See also Google Scholar, ResearchGate, or Semantic Scholar.

My ORCID is 0000-0002-4060-1738.

Equal contributions are denoted by *, and (equal) senior authorship by ^#.

Preprints

• Pretrain-test task alignment governs generalization in in-context learning
  Letey, M. I., Zavatone-Veth, J. A., Lu, Y. M., and Pehlevan, C.
  [arXiv]

• Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding
  Fernández del Castillo, J. C., Pashakhanloo, F., Murthy, V. N.^#, and Zavatone-Veth, J. A.^#
  [bioRxiv]

• A note on the dynamics of extended-context disordered kinetic spin models
  Zavatone-Veth, J. A. and Pehlevan, C.
  [arXiv]

• Dynamically learning to integrate in recurrent neural networks
  Bordelon, B., Cotler, J., Pehlevan, C., and Zavatone-Veth, J. A.
  [arXiv]

• Combining sampling methods with attractor dynamics in spiking models of head direction systems
  Pjanovic, V., Zavatone-Veth, J. A., Masset, P., Keemink, S. W.^#, and Nardin, M.^#
  [bioRxiv]

• Two-point deterministic equivalence for stochastic gradient dynamics in linear models
  Atanasov, A.*, Bordelon, B.*, Zavatone-Veth, J. A.*, Paquette, C., and Pehlevan, C.
  [arXiv]

• Spectral regularization for adversarially-robust representation learning
  Yang, S., Zavatone-Veth, J. A., and Pehlevan, C.
  [arXiv] [code]

• Scaling and renormalization in high-dimensional regression
  Atanasov, A., Zavatone-Veth, J. A., and Pehlevan, C.
  [arXiv] [code]

• Neural networks learn to magnify areas near decision boundaries
  Zavatone-Veth, J. A., Yang, S., Rubinfien, J. A., and Pehlevan, C.
  [arXiv] [code]

Articles

2025

• Data symmetries generate drifting similarity matrices in manifold-tiling neural codes
  Pashakhanloo, F., and Zavatone-Veth, J. A.
  Unifying Representations in Neural Models Workshop (UniReps), NeurIPS (2025).

• Perspective: summary statistics of learning
  Zavatone-Veth, J. A.^#, Bordelon, B.^#, and Pehlevan, C.^#
  Unifying Representations in Neural Models Workshop (UniReps), NeurIPS (2025).

• Summary statistics of learning link changing neural representations to behavior
  Zavatone-Veth, J. A.^#, Bordelon, B.^#, and Pehlevan, C.^#
  Frontiers in Neural Circuits 19:1618351 (2025).
  [link] [arXiv]
  Invited contribution to the Neuro-inspired computation Research Topic, edited by Takao Hensch and Kenny Blum.

• Asymptotic theory of in-context learning by linear attention
  Lu, Y. M., Letey, M. I., Zavatone-Veth, J. A.*, Maiti, A.*, and Pehlevan, C.
  Proceedings of the National Academy of Sciences of the United States of America (PNAS) 122 (28) e2502599122 (2025).
  [link] [arXiv] [code]

• Two-point deterministic equivalence for SGD in random feature models
  Atanasov, A.*, Bordelon, B.*, Zavatone-Veth, J. A.*, Paquette, C., and Pehlevan, C.
  Workshop on High-dimensional Learning Dynamics (HiLD), ICML 2025.
  [OpenReview]

• A model for place field reorganization during reward maximization
  Kumar, M. G., Bordelon, B., Zavatone-Veth, J. A., and Pehlevan, C.
  International Conference on Machine Learning (ICML) 42. (2025).
  [bioRxiv]

• Risk and cross validation in ridge regression with correlated samples
  Atanasov, A.*, Zavatone-Veth, J. A.*, and Pehlevan, C.
  International Conference on Machine Learning (ICML) 42. (2025).
  [arXiv] [code]

• A model for place field reorganization during reward maximization
  Kumar, M. G., Bordelon, B., Zavatone-Veth, J. A., and Pehlevan, C.
  Workshop on Representational Alignment (Re-Align), ICLR (2025).
  [OpenReview]

• Nadaraya-Watson kernel smoothing as a random energy model
  Zavatone-Veth, J. A.^#, and Pehlevan, C.
  Journal of Statistical Mechanics: Theory and Experiment 013404. (2025)
  [link] [arXiv]

2024

• Long Sequence Hopfield Memory
  Chaudhry, H. T., Zavatone-Veth, J. A., Krotov, D., and Pehlevan, C.
  Journal of Statistical Mechanics: Theory and Experiment 104024. (2024)
  [link]
  Invited contribution to the Machine Learning 2024 special issue; updated version of our NeurIPS 2023 paper.

• Learning curves for deep structured Gaussian feature models
  Zavatone-Veth, J. A., and Pehlevan, C.
  Journal of Statistical Mechanics: Theory and Experiment 104022. (2024)
  [link]
  Invited contribution to the Machine Learning 2024 special issue; updated version of our NeurIPS 2023 paper.

• Adversarially-robust representation learning through spectral regularization of features
  Yang, S., Zavatone-Veth, J. A., and Pehlevan, C.
  Workshop on Symmetry and Geometry in Neural Representations, NeurIPS (2024).
  [OpenReview]

• In-context learning by linear attention: exact asymptotics and experiments
  Lu, Y. M., Letey, M. I., Zavatone-Veth, J. A.*, Maiti, A.*, and Pehlevan, C.
  Workshop on Mathematics of Modern Machine Learning, NeurIPS (2024).
  [OpenReview]

• Partial observation can induce mechanistic mismatches in data-constrained RNNs
  Qian, W., Zavatone-Veth, J. A., Ruben, B. S., and Pehlevan, C.
  Workshop on NeuroAI, NeurIPS (2024)
  [OpenReview]

• Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics
  Qian, W., Zavatone-Veth, J. A., Ruben, B. S., and Pehlevan, C.
  Advances in Neural Information Processing Systems (NeurIPS) 37. (2024)
  [link] [bioRxiv]

• Statistical mechanics of Bayesian inference and learning in neural networks
  Zavatone-Veth, J. A.
  PhD dissertation, Department of Physics, Harvard University.
  [ProQuest] [Harvard DASH]

2023

• Long Sequence Hopfield Memory
  Chaudhry, H. T., Zavatone-Veth, J. A., Krotov, D., and Pehlevan, C.
  Associative Memory and Hopfield Networks Workshop Oral, NeurIPS (2023)
  [OpenReview]

• Neural circuits for fast Poisson compressed sensing in the olfactory bulb
  Zavatone-Veth, J. A.*, Masset, P.*, Tong, W. L., Zak, J. D., Murthy, V. N.^#, and Pehlevan, C.^#
  Advances in Neural Information Processing Systems (NeurIPS) 36. (2023)
  [link] [OpenReview] [bioRxiv] [code]

• Long Sequence Hopfield Memory
  Chaudhry, H. T., Zavatone-Veth, J. A., Krotov, D., and Pehlevan, C.
  Advances in Neural Information Processing Systems (NeurIPS) 36. (2023)
  [link] [OpenReview] [arXiv] [code]

• Learning curves for deep structured Gaussian feature models
  Zavatone-Veth, J. A., and Pehlevan, C.
  Advances in Neural Information Processing Systems (NeurIPS) 36. (2023)
  [link] [OpenReview] [arXiv]

• Replica method for eigenvalues of real Wishart product matrices
  Zavatone-Veth, J. A., and Pehlevan, C.
  SciPost Physics Core 6 (2): 026. (2023)
  [link] [arXiv]

2022

• Asymptotics of representation learning in finite Bayesian neural networks
  Zavatone-Veth, J. A., Canatar, A., Ruben, B. S., and Pehlevan, C.
  Journal of Statistical Mechanics: Theory and Experiment 114008. (2022)
  [link]
  Invited contribution to the Machine Learning 2022 special issue; updated version of our NeurIPS paper.

• Contrasting random and learned features in deep Bayesian linear regression
  Zavatone-Veth, J. A., Tong, W. L., and Pehlevan, C.
  Machine Learning and the Physical Sciences Workshop, NeurIPS. (2022)
  [link]

• Training shapes the curvature of shallow neural network representations
  Zavatone-Veth, J. A.*, Rubinfien, J. A.*, and Pehlevan, C.
  Symmetry and Geometry in Neural Representations (NeurReps) Workshop, NeurIPS. (2022)
  [OpenReview]

• Natural gradient enables fast sampling in spiking neural networks
  Masset, P.*, Zavatone-Veth, J. A.*, Connor, J. P., Murthy, V. N.^#, and Pehlevan, C.^#
  Advances in Neural Information Processing Systems (NeurIPS) 35. (2022)
  [link] [OpenReview] [bioRxiv] [code]

• Excitatory and inhibitory neural dynamics jointly tune motion detection
  Gonzalez-Suarez, A. D., Zavatone-Veth, J. A., Chen, J., Matulis, C., Badwan, B. A., and Clark, D. A.
  Current Biology 32 (17) 3659-3675. (2022)
  [link] [bioRxiv] [code]

• Contrasting random and learned features in deep Bayesian linear regression
  Zavatone-Veth, J. A., Tong, W. L., and Pehlevan, C.
  Physical Review E 105 (6): 064118. (2022)
  [link] [arXiv]

• On neural network kernels and the storage capacity problem
  Zavatone-Veth, J. A., and Pehlevan, C.
  Neural Computation 34 (5): 1136–1142. (2022)
  [link] [arXiv]

• Parallel locomotor control strategies in mice and flies
  Gonçalves, A. I.*, Zavatone-Veth, J. A.*, Carey, M. R.^#, and Clark, D. A.^#
  Current Opinion in Neurobiology 73: 102516. (2022)
  [link] [arXiv]

• Drifting neuronal representations: Bug or feature?
  Masset, P.*, Qin, S.*, and Zavatone-Veth, J. A.*
  Biological Cybernetics 116: 253-266. (2022)
  [link]

2021

• Depth induces scale-averaging in overparameterized linear Bayesian neural networks
  Zavatone-Veth, J. A., and Pehlevan, C.
  55th Asilomar Conference on Signals, Systems, and Computers. (2021)
  [link] [arXiv]

• Asymptotics of representation learning in finite Bayesian neural networks
  Zavatone-Veth, J. A., Canatar, A., Ruben, B. S., and Pehlevan, C.
  Advances in Neural Information Processing Systems (NeurIPS) 34. (2021)
  [link] [OpenReview] [arXiv] [code]

• Exact marginal prior distributions of finite Bayesian neural networks
  Zavatone-Veth, J. A., and Pehlevan, C.
  Advances in Neural Information Processing Systems (NeurIPS) 34 Spotlight. (2021)
  [link] [OpenReview] [arXiv] [code]

• Activation function dependence of the storage capacity of treelike neural networks
  Zavatone-Veth, J. A., and Pehlevan, C.
  Physical Review E (Letter) 103 (2): L020301. (2021)
  [link] [arXiv]

2020

• Statistical structure of the trial-to-trial timing variability in synfire chains
  Obeid, D., Zavatone-Veth, J. A., and Pehlevan, C.
  Physical Review E 102 (5): 052406. (2020)
  [link] [bioRxiv]

• Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila
  DeAngelis, B. D.*, Zavatone-Veth, J. A.*, Gonzalez-Suarez, A. D., and Clark, D. A.
  eLife 9: e54183. (2020)
  [link] [code]

• A minimal synaptic model for direction selective neurons in Drosophila
  Zavatone-Veth, J. A., Badwan, B. A., and Clark, D. A.
  Journal of Vision 20 (2): 2. (2020)
  [link] [bioRxiv] [code]

2019

• Using slow frame rate imaging to extract fast receptive fields
  Mano, O., Creamer, M. S., Matulis, C. A., Salazar-Gatzimas, E., Chen, J., Zavatone-Veth, J. A., and Clark, D. A.
  Nature Communications 10: 4979. (2019)
  [link] [code]

• Dynamic nonlinearities enable direction opponency in Drosophila elementary motion detectors
  Badwan, B. A., Creamer, M. S., Zavatone-Veth, J. A., and Clark, D. A.
  Nature Neuroscience 22: 1318–1326. (2019)
  [link] [code]

• The manifold structure of limb coordination in walking Drosophila
  DeAngelis, B. D.*, Zavatone-Veth, J. A.*, and Clark, D. A.
  eLife 8: e46409. (2019)
  [link] [erratum] [code]