Papers

Preprints:

D Qian, Q Liang, IR Fiete. Modular connectivity in neural networks emerges from Poisson noise-motivated regularisation, and promotes robustness and compositional generalisation. arXiv:2512.13707 (2025).

A Huang, M Ostrow, SH Singh, L Kozachkov, IR Fiete, K Rajan. InputDSA: Demixing then Comparing Recurrent and Externally Driven Dynamics. arXiv:2510.25943 (2025).

M Schartner, A Liu, Laboratory International Brain, IR Fiete. Spatially distributed and regionally unbound cellular resolution brain-wide processing loops in mice. biorxiv 10.1101/2025.07.30.667641 (2025).

JD Hwang, T Kumar, SJ Lee, A Agrawal, H Palangi, A Kumar, IR Fiete+, PP Liang+. Learn globally, speak locally: Bridging the gaps in multilingual reasoning. arXiv 2507.05418 (2025). [+co-senior]

L Chen, LL Dong, H Shin, F Shahid, T Malone, Y Ma, SO Vasu, NW Tien, Kyle Cekada, Lucy Anderson, Sarthak Chandra+, Ila Fiete+, Veronica A Alvarez+, Yi Gu+. Slow synaptic plasticity from the hippocampus underlies gradual mapping and fragmentation of novel spaces by grid cells. bioRxiv 10.1101/2025.07.30.667696 (2025). [+co-senior]

S Duan*, LL Dong*, IR Fiete. From Synapses to Dynamics: Obtaining Function from Structure in a Connectome Constrained Model of the Head Direction Circuit. bioRxiv 2025.05.26.655406 (2025). [*co-first authors]

AJ Eisen, AG Bardon, JJ Ballesteros, AM Bastos, JA Donoghue, MK Mahnke, SL Brincat, J Roy, Y Ishizawa, E Brown, IR Fiete+, EK Miller+. Similar destabilization of neural dynamics under different general anesthetics. bioRxiv 10.1101/2025.08.21.671540 (2025). [+co-senior authors]

AJ Eisen, M Ostrow, S Chandra, L Kozachkov, EK Miller, IR Fiete. Characterizing control between interacting subsystems with deep Jacobian estimation. arXiv:2507.01946 (2025).

A Zahorodnii, C Wang, B Stankovits, C Moraitaki, G Chau, A Barbu, B Katz, IR Fiete. Neuroprobe: Evaluating Intracranial Brain Responses to Naturalistic Stimuli. arXiv:2509.21671 (2025).

A Zahorodnii, JJF van den Bosch, I Charest, C Summerfield, IR Fiete. Paper Quality Assessment based on Individual Wisdom Metrics from Open Peer Review. arXiv:2501.13014D (2025).

S Chandra*, M Khona*, T Konkle, IR Fiete. Self-organized emergence of modularity, hierarchy, and mirror reversals from competitive synaptic growth in a developmental model of the visual pathway. bioRxiv 2024.01.07.574543 (2024). [*co-first]

A. Boopathy, A. Muppidi, P. Yang, A. Iyer, W. Yue, I.R. Fiete. Permutation Invariant Learning with High-Dimensional Particle Filters arXiv:2410.22695 (2024).

J. Hwang, B. Cheung, Z.W. Hong, A. Boopathy, P. Agrawal, I.R. Fiete. ImageNet-RIB Benchmark: Large Pre-Training Datasets Don’t Guarantee Robustness after Fine-Tuning arXiv:2410.21582.

A. Boopathy, I.R. Fiete. Unified Neural Network Scaling Laws and Scale-time Equivalence. arXiv:2409.05782 (2024).

A. Boopathy, S. Jiang, W. Yue, J. Hwang, A. Iyer, I.R. Fiete. Breaking Neural Network Scaling Laws with Modularity. arXiv:2409.05780 (2024).

A. Boopathy, W. Yue, J. Hwang, A. Iyer, I.R. Fiete. Towards Exact Computation of Inductive Bias. arXiv:2406.15941 (2024).

A. Boopathy, A. Muppidi, P. Yang, A. Iyer, W. Yue, I.R. Fiete. Resampling-free Particle Filters in High-dimensions. arXiv:2404.13698

J.D. Hwang, Z.W. Hong, E. Chen, A. Boopathy, P. Agrawal, I.R. Fiete. Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity. arXiv:2310.17537 (2023).

R. Schaeffer, M. Khona, Z. Robertson, A. Boopathy, K. Pistunova, J.W. Rocks, I.R. Fiete, S. Koyejo. Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. arXiv 2303.14151 (2023).

T. McCourt, I.R. Fiete, I.L. Chuang. Noisy dynamical systems evolve error-correcting codes and modularity. arXiv (2023). link

D. Mulders, M. Yim, J.S. Lee, A.K. Lee, T. Taillefumier, I.R. Fiete. A structured scaffold underlies activity in the hippocampus. bioRxiv (2021). link

M. Klukas, S. Sharma, Y. Du, T. Lozano Perez, L. Kaelbling, I.R. Fiete. Fragmented spatial maps: state abstraction and efficient planning from surprisal. bioRxiv (2021). link

J.H.J. Kim, I.R. Fiete, D. Schwab. Superlinear precision and memory in simple population codes. arXiv (2020). link

I. Kanitscheider and I.R. Fiete. Emergence of dynamically reconfigurable hippocampal responses by learning to perform probabilistic spatial reasoning. bioRxiv 10.1101/231159 (2017).
link

Journals (by year):

Q Liang, D Qian, L Ziyin, I Fiete. Compositional Generalization via Forced Rendering of Disentangled Latents. Proc. ICML (2025).

D Angelaki, et al. A brain-wide map of neural activity during complex behaviour. Nature (2025).

C Findling, et al. Brain-wide representations of prior information in mouse decision-making. Nature (2025)

F Claudi*, S. Chandra*, I.R. Fiete. A theory and recipe to construct general and biologically plausible integrating continuous attractor neural networks. bioRxiv 10.1101/2025.05.07.652608 (2025) and Elife (2025). [*co-first authors]

Qian, I.R. Fiete. Fundamental performance bounds on reservoir computing. arXiv:2410.20393 (2024) and Physical Review E (2025).

SJ Gershman, I Fiete, K Irie. Key-value memory in the brain. arXiv:2501.02950 (2025) and Neuron (2025).

Q Liang, Z Liu, M Ostrow, I Fiete. How Diffusion Models Learn to Factorize and Compose. Proc. NeurIPS (2024).

M. Khona, S. Chandra, I.R. Fiete. Global modules robustly emerge from local interactions and smooth gradients. bioRxiv (2023) and Nature (2025).

S. Chandra*, S. Sharma*, R. Chaudhuri, I.R. Fiete. Episodic and associative memory from spatial scaffolds in the hippocampus. Nature, 1-13 (2025). [*co-first authors]

Y Xie, J Hwang, C Brody, D Tank, IR Fiete. A Multi-Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision-Making. bioRxiv 2025.05.29.656671 (2025) and Proc. ICML (2025).

S Duan, M Khona, A Iyer, R Schaeffer, IR Fiete. Uncovering Latent Memories in Large Language Models. ICLR (2025).

J. Hwang, Z.W. Hong, E. Chen, A. Boopathy, P. Agrawal, I.R. Fiete. Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building. arXiv 2307.05793 (2023) and Trans. MLR (2024).

A. Zlokapa, A.K. Tan, J.M. Martyn, I.R. Fiete, M. Tegmark, I.L. Chuang. Fault-tolerant neural networks from biological error correction codes. arXiv (2022) and Physical Review E 110, 054303 (2024).

J. Voigts, I. Kanitscheider, N.J. Miller, E.H.S. Toloza, J.P. Newman, I.R. Fiete, M.T. Harnett. Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex. Neuron (2024) and bioRxiv (2022). link

L.L. Dong, I.R. Fiete. Grid Cells in Cognition: Mechanisms and Function. Annual Review of Neuroscience 47 (2024).

A. Eisen, L. Kozachkov, A.M. Bastos, J.A. Donoghue, M.K. Mahnke, S.L. Brincat, S. Chandra, E.N. Brown, I.R. Fiete+, E.K. Miller+. Propofol anesthesia destabilizes neural dynamics across cortex. bioRxiv 10.1101/2023.11.24.568595 (2023) and Neuron (2024). [+co-senior authors]

S. Neupane, I.R. Fiete, M. Jazayeri. Mental navigation in the primate entorhinal cortex. arXiv (2022) and Nature (2024). link

X. Yi, J. Hwang, C. Brody, D. Tank, I.R. Fiete. A Multi-Region Brain Model to Shed Light on the Role of Hippocampus in Spatially Embedded Decision Tasks. Conference on Cognitive Computational Neuroscience (2024).

R. Wang, J. Hwang, A. Boopathy, I.R. Fiete. Rapid Learning without Catastrophic Forgetting in the Morris Water Maze. International Conference on Machine Learning (2024).

A. Kirjner, J. Yim, R. Samusevich, T. Jaakkola, R. Barzilay, I.R. Fiete. Improving protein optimization with smoothed fitness landscapes. arXiv (2023) and ICLR (2024). MITNews

J. Hwang, S. Neupane, M. Jazayeri, I.R. Fiete. Generalizable Relational Inference with Cognitive Maps in a Hippocampal Model and in Primates. NeurIPS Workshop on Associative Memory & Hopfield Networks (2023).

Z. Liu, M. Khona, I.R. Fiete, M. Tegmark. Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks. arXiv 2310.07711 (2023) and NeurIPS Workshop on Symmetry and Geometry in Neural Representations (2023).

M. Ostrow, A. Eisen, L. Kozachkov, I.R. Fiete. Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis arXiv 2306.10168 (2023) and NeurIPS (2023).

A. Boopathy, K. Liu, J. Hwang, S. Ge, A. Mohammedsaleh, I.R. Fiete. Model-agnostic measure of generalization difficulty. ICML, 2857-2884 (2023).

R. Schaeffer*, M. Khona*, T.Ma, C. Eyzaguirre, S. Koyejo, I.R. Fiete. Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. arXiv:2311.02316 (2023) and NeurIPS (2023). [*co-first authors]

J.J. Pattadkal, B.V. Zemelman, I.R. Fiete, N. Priebe. Primate neocortex performs balanced sensory amplification. bioRxiv (2022) and Neuron (2023). link

J. Hwang, S. Neupane, M. Jazayeri, I.R. Fiete. A Grid Cell-Place Cell Scaffold Allows Rapid Learning and Generalization at Multiple Levels on Mental Navigation Tasks. Conference on Cognitive Computational Neuroscience (2023).

R. Schaeffer, Z. Robertson, A. Boopathy, M. Khona, I.R. Fiete, A. Gromov, S. Koyejo. Divergence at the Interpolation Threshold: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. NeurIPS Workshop on Mathematics of Modern Machine Learning (2023).

S Duan, M Khona, A Bertagnoli, S Chandra, I Fiete. See and Copy: Generation of complex compositional movements from modular and geometric RNN representations. NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PLMR (2023) and arxiv arXiv:2210.02521 (2022).

R. Schaeffer, M. Khona, A. Bertagnoli, S. Koyejo, I.R. Fiete. Testing Assumptions Underlying a Unified Theory for the Origin of Grid Cells. arXiv:2311.16295 (2023) and NeurIPS 2023 AI for Science Workshop (2023).

A. Boopathy, K. Liu, J. Hwang, S. Ge, A. Mohammedsaleh, I.R. Fiete. Model-agnostic measure of generalization difficulty. ICML (2023). link blog video

M. Ostrow, A. Eisen, L. Kozachkov, I.R. Fiete. Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis. CCCN, arXiv (2023). link

M. Khona*, S. Chandra*, J.J. Ma, I.R. Fiete. Winning the lottery with neurobiology: faster learning on many cognitive tasks with fixed sparse RNNs. bioRxiv (2022), Neural Comp. 1-20 (2023). [*co-first author] link

R. Schaeffer, M. Khona, Z. Robertson, A. Boopathy, K. Pistunova, J.W. Rocks, I.R. Fiete, O. Koyejo. Double descent demystified: Identifying, interpreting & ablating the sources of a deep learning puzzle. CoRR, arXiv (2023). link

S. Duan, M. Khona, A. Bertagnoli, S. Chandra, I.R. Fiete. See and copy: Generation of complex compositional movements from modular and geometric RNN representations. arXiv (2023). NeurIPS Workshop on Symmetry and Geometry in Neural Representations link

R. Schaeffer, M. Khona, I.R. Fiete. No free lunch with deep learning in Neuroscience: A case study through models of the entorhinal-hippocampal circuit. NeurIPS. Eds. A.H. Oh, A. Agarwal, D. Belgrave, K. Cho (2022). link

M. Khona and I.R. Fiete. Attractor and integrator networks in the brain. Nature Reviews Neuroscience (2022). link | bioRxiv link

A. Boopathy & I. R. Fiete. How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective. ICML, PMLR (2022). link

S. Sharma, S. Chandra, I.R. Fiete. Content-addressable memory without catastrophic forgetting by heteroassociation with a fixed scaffold. ICML, PMLR (2022). link

R. Schaeffer, Y. Du, G.K. Liu, I.R. Fiete. Streaming Inference for Infinite Feature Models. Proceedings, ICML, PMLR (2022). link

S. Sharma, A. Curtis, M. Kryven, J. Tenenbaum, I.R. Fiete. Map Induction: Compositional spatial submap learning for efficient exploration in novel environments. ICLR (2022). link

Neurotensin orchestrates valence assignment in the amygdala. H. Li et al. Nature (2022). link

Cortical ensembles orchestrate social competition through hypothalamic outputs. N. Padilla-Coreano, et al. Nature (2022). link

J. Gjorgjieva, I.R. Fiete. Theoretical and computational approaches to decipher brain function from molecules to behavior. Curr. Op. Neurobiology (2021). link

R. Schaeffer, B. Bordelon, M. Khona, W. Pan, I.R. Fiete. Efficient online inference for nonparametric mixture models. Conference on Uncertainty in AI, In PMLR (2021). pdf

M. Yim, L. Sadun, I.R. Fiete, T. Taillefumier. Place cell capacity and volatility with grid-like inputs. Elife (2021). pdf | link

The International Brain Laboratory, et al. Standardized and reproducible measurement of decision-making in mice. eLife 10:e63711 (2021). link

H. Sanders, M. Wilson, M. Klukas, S. Sharma. I.R. Fiete. Efficient Inference in Structured Spaces. Cell 183(5):1147-1148(2020). link

R. Schaeffer, M. Khona, L. Meshulam, The International Brain Laboratory, I.R. Fiete. Reverse-engineering Recurrent Neural Network solutions to a hierarchical inference task for mice. NeurIPS (2020). link

L.F. Abbott et al. The mind of a mouse. Cell 182(6) (2020). link

B. Kriener*, R. Chaudhuri*, I.R. Fiete. Robust parallel decision-making in neural circuits with nonlinear inhibition. PNAS (2020). [*co-first author]
link

A. Das and I.R. Fiete. Systematic errors in connectivity inferred from activity in strongly coupled recurrent circuits. Nature Neurosci. (2020).
link | bioRxiv link

M. Stangl*, I. Kanitscheider*, M. Riemer, I.R. Fiete+, and T. Wolbers+. Sources of path integration error in young and aging humans. Nature Communications (2020). [*co-first author; +co-senior author]
link

M. Klukas, M. Lewis, I.R. Fiete. Flexible representation and memory of higher-dimensional cognitive variables with grid cells. PLoS Comp. Biol. (2020).
link

R. Chaudhuri, I.R. Fiete. Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes. Proc. NeurIPS (2019). link

R. Chaudhuri, B. Gercek*, B. Pandey*, A. Peyrache, I.R. Fiete. The intrinsic population dynamics of a canonical cognitive circuit. Nature Neurosci. (2019). [*co-second author]
link | bioRxiv link

S.G. Trettel*, J.B. Trimper*, E. Hwaun, I.R. Fiete, L.L. Colgin. Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors. Nature Neurosci. 22, 609–617 (2019). [*co-first author]
link | pdf

C. Roth, I. Kanitscheider, I.R. Fiete. Kernel RNN Learning (KeRNL). Proceedings of ICLR (2019).
link

Y. Gu, S. Lewallen, A. Kinkhabwala, C. Domnisoru, K. Yoon, J. Gauthier, I.R. Fiete, and D.W. Tank. A map-like micro-organization of grid cells in the medial entorhinal cortex. Cell 175, 736–750 (2018).
link | pdf

J. Widloski, M. Marder, and I.R. Fiete. Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells. eLife 10.7554/eLife.33503.001 (2018).
link

The International Brain Laboratory (consortium including the Fiete lab). An International Laboratory for Systems and Computational Neuroscience. Neuron (2017).
link |pdf

I. Kanitscheider and I.R. Fiete. Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems. In Advances in NIPS (2017).
link

O.O. Koyluoglu, Y. Pertzov, S. Manohar, M. Husain, I.R. Fiete. Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity. eLife 2017;6:e22225 (2017).
link

I. Kanitscheider and I.R. Fiete. Toward a comprehensive functional understanding of the brain’s spatial navigation system. Curr. Opinion in Systems Biol. 3 186-194 (2017).
link | pdf

R. Chaudhuri and I.R. Fiete. Computational principles of memory. Nature Neurosci. 19, 394-403 (2016).
link | pdf

K Yoon*, S. Lewallen*, A. Kinkhabwalla, D.W. Tank+ and I.R. Fiete+. Grid cell responses in 1D environments assessed as slices through a 2D lattice. Neuron 89(5), 1086-1099 (2016) [*co-first author; +co-senior author]
link | pdf

Y. Yoo, O.O. Koyluoglu, S. Vishwanath, I. R. Fiete. Multi-periodic neural coding for adaptive information transfer. Theoretical Computer Science 633, 37-53 (2016).
link | pdf

X. Chen, Q. He, J.W. Kelly, I.R. Fiete and T.P. McNamara. Bias in human path integration is predicted by properties of grid cells. Current Biology 25, 1771–1776 (2015).
link | pdf

I. Fiete, D. Schwab and N.M. Tran. A binary Hopfield network with 1/log(n) information rate and applications to grid cell decoding. Workshop paper for Biological Distributed Algorithms, Austin TX (2014).
pdf

J. Widloski and I. R. Fiete. A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity. Neuron 83(2): 481–495 (2014).
link | pdf | SI pdf

K. Yoon, M. Buice, C. Barry, N. Burgess, and I. R. Fiete. Specific evidence of low dimensional continuous attractor dynamics in grid cells. Nature Neurosci. 16, 1077-1084 doi:10.1038/nn.3450 (2013).
link | pdf

J. Widloski and I. R. Fiete. How does the brain solve the computational problems of spatial navigation? Bookchapter in Space, Time, and Memory in the Hippocampal Formation. Eds. D. Derdikman and J. Knierim. Springer-Verlag. (2013).
pdf

Y. Burak and I. R. Fiete. Fundamental limits on persistent activity in networks of noisy neurons. PNAS 109 (43): 17645-17650 (2012).
pdf | SI pdf

Y. Yoo, O. O. Koyluoglu, S. Vishwanath and I. R. Fiete. Dynamic shift-map coding with side information at the decoder. 50th Annual Allerton Conference on Communication, Control, and Computing (2012).
pdf

S. Sreenivasan and I. R. Fiete. Grid cells generate an analog error-correcting code for singularly precise neural computation. Nature Neurosci. 14, 1330-1337 doi:10.1038/nn.2901 (2011).
pdf | SI pdf

I. R. Fiete. Losing phase. Neuron 66(3): 331-34 (2010).
pdf

I. R. Fiete, W. Senn, C. Wang, R. H. R. Hahnloser. Spike time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity. Neuron 65(4): 563-576 (2010).
pdf

Y. Burak and I. R. Fiete. Accurate path integration in continuous attractor network models of grid cells. PLoS Comp. Biol. 5(2) (2009).
pdf

I. R. Fiete and H. S. Seung. Birdsong Learning. In Encyclopedia of Neuroscience (L. Squire, Editor). Amsterdam: Elsevier Academic Press, pp. 227-239 (2009). (Originally available online 2008 on Science Direct.)
pdf

M. Murthy, I. R. Fiete, and G. Laurent. Testing odor response stereotypy in the Drosophila mushroom body. Neuron 59(6):1009-23 (2008).
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Related preview: S. Cachero and G. Jefferis. Drosophila olfaction: The end of stereotypy? Neuron 59(6): 843-845 (2008).
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P.E. Welinder, Y. Burak and I. R. Fiete. Grid cells: The position code, neural network models of activity, and the problem of learning. Hippocampus 18(12):1283-300 (2008).
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I. R. Fiete, Y. Burak and T. Brookings. What grid cells encode about rat position. J. Neuroscience 28, 6856-6871 (2008).
pdf

I. R. Fiete, M.S. Fee and H. S. Seung. Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. J. Neurophysiology 98, 2038 2057 (2007).
pdf

Y. Burak and I. R. Fiete. Do we understand the emergent dynamics of grid cell activity? J. Neuroscience 26, 9352-9354 (2006).
pdf

I. R. Fiete and H. S. Seung. Gradient learning in spiking neural networks by dynamic perturbation of conductances. Physical Review Letters 97, 048104 (2006).
pdf

I. R. Fiete, R.H.R Hahnloser, M.S. Fee and H. S. Seung. Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. J. Neurophysiology 92, 2274 (2004).
pdf

S. Sullow, I.R. Prasad, M.C. Aronson et al. Metallization and magnetic order in EuB_6. Physical Review B 62, 11626 (2000).
pdf

S. Sullow, I.R. Prasad, S. Bogdanovich et al. Magnetotransport in the low carrier density ferromagnet EuB_6. J. Applied Physics 87, 5591 (2000).
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S. Sullow, I.R. Prasad, M.C. Aronson et al. Magnetic order of EuB_6. Physical Review B 57, 5860 (1998).
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Categorized by topic

Theoretical ML

Q Liang, D Qian, L Ziyin, I Fiete. Compositional Generalization via Forced Rendering of Disentangled Latents. Proc. ICML (2025).

Q Liang, Z Liu, M Ostrow, I Fiete. How Diffusion Models Learn to Factorize and Compose. Proc. NeurIPS (2024).

A. Boopathy, A. Muppidi, P. Yang, A. Iyer, W. Yue, I.R. Fiete. Permutation Invariant Learning with High-Dimensional Particle Filters arXiv:2410.22695 (2024).

A. Boopathy, I.R. Fiete. Unified Neural Network Scaling Laws and Scale-time Equivalence. arXiv:2409.05782 (2024).

A. Boopathy, S. Jiang, W. Yue, J. Hwang, A. Iyer, I.R. Fiete. Breaking Neural Network Scaling Laws with Modularity. arXiv:2409.05780 (2024).

A. Boopathy, W. Yue, J. Hwang, A. Iyer, I.R. Fiete. Towards Exact Computation of Inductive Bias. arXiv:2406.15941 (2024).

A. Boopathy, A. Muppidi, P. Yang, A. Iyer, W. Yue, I.R. Fiete. Resampling-free Particle Filters in High-dimensions. arXiv:2404.13698

R. Schaeffer, Z. Robertson, A. Boopathy, M. Khona, I.R. Fiete, A. Gromov, S. Koyejo. Divergence at the Interpolation Threshold: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. NeurIPS Workshop on Mathematics of Modern Machine Learning (2023).

A. Boopathy, K. Liu, J. Hwang, S. Ge, A. Mohammedsaleh, I.R. Fiete. Model-agnostic measure of generalization difficulty. ICML (2023). link blog video

T. McCourt, I.R. Fiete, I.L. Chuang. Noisy dynamical systems evolve error-correcting codes and modularity. arXiv (2023). link

A. Zlokapa, A.K. Tan, J.M. Martyn, I.R. Fiete, M. Tegmark, I.L. Chuang. Biological error correction codes generate fault-tolerant neural networks. arXiv (2022). link

A. Boopathy & I. R. Fiete. Gradient-trained weights in wide neural networks align layerwise to error-scaled input correlations. arXiv (2021). link

Biologically plausible gradient learning

A. Boopathy & I. R. Fiete. Gradient-trained weights in wide neural networks align layerwise to error-scaled input correlations. arXiv (2021). link

C. Roth, I. Kanitscheider, I.R. Fiete. Kernel RNN Learning (KeRNL). Proceedings of ICLR (2019).
link

I. R. Fiete, M.S. Fee and H. S. Seung. Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. J. Neurophysiology 98, 2038 2057 (2007).
pdf

I. R. Fiete and H. S. Seung. Gradient learning in spiking neural networks by dynamic perturbation of conductances. Physical Review Letters 97, 048104 (2006).
pdf

Module/structure emergence

M. Khona, S. Chandra, I.R. Fiete. Global modules robustly emerge from local interactions and smooth gradients. bioRxiv (2023) and Nature (2025).

Q Liang, Z Liu, M Ostrow, I Fiete. How Diffusion Models Learn to Factorize and Compose. Proc. NeurIPS (2024).

T. McCourt, I.R. Fiete, I.L. Chuang. Noisy dynamical systems evolve error-correcting codes and modularity. arXiv (2023). link

J. Widloski and I. R. Fiete. A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity. Neuron 83(2): 481–495 (2014).
link | pdf | SI pdf

Continuous attractors in the brain

M. Khona and I.R. Fiete. Attractor and integrator networks in the brain. Nature Reviews Neuroscience (2022). link | bioRxiv link

R. Chaudhuri, B. Gercek*, B. Pandey*, A. Peyrache, I.R. Fiete. The intrinsic population dynamics of a canonical cognitive circuit. Nature Neurosci. (2019). [*co-second author]
link | bioRxiv link

Error-correcting codes

S. Chandra*, S. Sharma*, R. Chaudhuri, I.R. Fiete. High-capacity flexible hippocampal associative and episodic memory enabled by prestructured ”spatial” representations. bioRxiv 10.1101/2023.11.28.568960 (2023). [*co-first authors]

M. Yim, L. Sadun, I.R. Fiete, T. Taillefumier. Place cell capacity and volatility with grid-like inputs. Elife (2021). pdf | link

M. Klukas, M. Lewis, I.R. Fiete. Flexible representation and memory of higher-dimensional cognitive variables with grid cells. PLoS Comp. Biol. (2020).
link

R. Chaudhuri, I.R. Fiete. Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes. Proc. NeurIPS (2019). link

Y. Yoo, O.O. Koyluoglu, S. Vishwanath, I. R. Fiete. Multi-periodic neural coding for adaptive information transfer. Theoretical Computer Science 633, 37-53 (2016).
link | pdf

I. R. Fiete, Y. Burak and T. Brookings. What grid cells encode about rat position. J. Neuroscience 28, 6856-6871 (2008).
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Inferring neural connectivity

L.F. Abbott, D.D. Bock, E.M. Callaway, W. Denk, C. Dulac, A.L. Fairhall, I.R. Fiete, K.M. Harris, M. Helmstaedter, V. Jain, N. Kasthuri, Y. LeCun, J.W. Lichtman, P.B. Littlewood, L. Luo, J.H.R. Maunsell, R.C. Reid, B.R. Rosen, G.M. Rubin, T.J. Sejnowski, H.S. Seung, K. Svoboda, D.W. Tank, D. Tsao, D.C. Van Essen. The mind of a mouse. Cell 182(6) (2020). link

A. Das and I.R. Fiete. Systematic errors in connectivity inferred from activity in strongly coupled recurrent circuits. Nature Neurosci. (2020).
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J. Widloski, M. Marder, and I.R. Fiete. Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells. eLife 10.7554/eLife.33503.001 (2018).
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M. Murthy, I. R. Fiete, and G. Laurent. Testing odor response stereotypy in the Drosophila mushroom body. Neuron 59(6):1009-23 (2008).
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Related preview: S. Cachero and G. Jefferis. Drosophila olfaction: The end of stereotypy? Neuron 59(6): 843-845 (2008).
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Memory

S. Sharma, S. Chandra, I.R. Fiete. Content-addressable memory without catastrophic forgetting by heteroassociation with a fixed scaffold. Proc ICML (2022).

R. Chaudhuri and I.R. Fiete. Computational principles of memory. Nature Neurosci. 19, 394-403 (2016).
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Y. Burak and I. R. Fiete. Fundamental limits on persistent activity in networks of noisy neurons. PNAS 109 (43): 17645-17650 (2012).
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R. Schaeffer, B. Bordelon, M. Khona, W. Pan, I.R. Fiete. Efficient online inference for nonparametric mixture models. Conference on Uncertainty in AI, In Proc. Machine Learning Research (2021). pdf

Decision making

The International Brain Laboratory, et al. Standardized and reproducible measurement of decision-making in mice. eLife 10:e63711 (2021). link

B. Kriener*, R. Chaudhuri*, I.R. Fiete. Robust parallel decision-making in neural circuits with nonlinear inhibition. PNAS (2020). [*co-first author]
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The International Brain Laboratory (consortium including the Fiete lab). An International Laboratory for Systems and Computational Neuroscience. Neuron (2017).
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Navigation circuits and spatial cognition

S. Sharma, A. Curtis, M. Kryven, J. Tenenbaum, I.R. Fiete. Map Induction: Compositional spatial submap learning for efficient exploration in novel environments. To appear, Proc. ICLR (2022). arXiv link

J. Widloski, M. Marder, and I.R. Fiete. Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells. eLife 10.7554/eLife.33503.001 (2018).
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I. Kanitscheider and I.R. Fiete. Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems. In Advances in NIPS (2017).
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I. Kanitscheider and I.R. Fiete. Toward a comprehensive functional understanding of the brain’s spatial navigation system. Curr. Opinion in Systems Biol. 3 186-194 (2017).
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X. Chen, Q. He, J.W. Kelly, I.R. Fiete and T.P. McNamara. Bias in human path integration is predicted by properties of grid cells. Current Biology 25, 1771–1776 (2015).
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J. Widloski and I. R. Fiete. A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity. Neuron 83(2): 481–495 (2014).
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‘J. Widloski and I. R. Fiete. How does the brain solve the computational problems of spatial navigation? Bookchapter in Space, Time, and Memory in the Hippocampal Formation. Eds. D. Derdikman and J. Knierim. Springer-Verlag. (2013).
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I. R. Fiete, Y. Burak and T. Brookings. What grid cells encode about rat position. J. Neuroscience 28, 6856-6871 (2008).
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P.E. Welinder, Y. Burak and I. R. Fiete. Grid cells: The position code, neural network models of activity, and the problem of learning. Hippocampus 18(12):1283-300 (2008).
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Y. Burak and I. R. Fiete. Accurate path integration in continuous attractor network models of grid cells. PLoS Comp. Biol. 5(2) (2009).
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Y. Burak and I. R. Fiete. Do we understand the emergent dynamics of grid cell activity? J. Neuroscience 26, 9352-9354 (2006).
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I. R. Fiete. Losing phase. Neuron 66(3): 331-34 (2010).
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Condensed-matter physics

S. Sullow, I.R. Prasad, M.C. Aronson et al. Metallization and magnetic order in EuB_6. Physical Review B 62, 11626 (2000).
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S. Sullow, I.R. Prasad, S. Bogdanovich et al. Magnetotransport in the low carrier density ferromagnet EuB_6. J. Applied Physics 87, 5591 (2000).
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S. Sullow, I.R. Prasad, M.C. Aronson et al. Magnetic order of EuB_6. Physical Review B 57, 5860 (1998).
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