Publications
Peer-reviewed articles
When and why does motor preparation arise in recurrent neural network models of motor control?
bioRXiv, 2023
A recurrent network model of planning explains hippocampal replay and human behavior
bioRXiv, 2023
Fisher-Legendre (FishLeg) optimization of deep neural networks
ICLR (notable 25%), 2023
Adaptive erasure of spurious sequences in sensory cortical circuits
Neuron, 2022
iLQR-VAE: control-based learning of input-driven dynamics with applications to neural data
ILCR (oral), 2022
Optimal anticipatory control as a theory of motor preparation: a thalamocortical circuit model
Neuron, 2021
Natural continual learning: success is a journey, not (just) a destination
NeurIPS, 2021
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models
NeurIPS, 2021
Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference
Nature Neuroscience, 2020
Efficient communication over complex dynamical networks: the role of matrix non-normality
Science Advances, 2020
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data
NeurIPS, 2020
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data
NeurIPS (oral), 2020
Neuroscience out of control: control-theoretic perspectives on neural circuit dynamics
Current Opinion in Neurobiology, 2019
Motor primitives in space and time via targeted gain modulation in cortical networks
Nature Neuroscience, 2018
Information transmission in dynamical networks: the normal network case
IEEE Conference on Decision and Control, 2018
Null ain’t dull: new perspectives on motor cortex
Trends in Cognitive Sciences, 2018
The dynamical regime of sensory cortex: stable dynamics around a single stimulus-tuned attractor account for patterns of noise variability
Neuron, 2018
Exact natural gradient in deep linear networks and application to the nonlinear case
NeurIPS, 2018
Inhibitory plasticity: balance, control, and codependence
Annu. Rev. Neurosci., 2017
Optimal control of transient dynamics in balanced networks supports generation of complex movements
Neuron, 2014
Analog memories in a balanced rate-based network of E/I neurons
NIPS (oral), 2014
Fast sampling-based inference in balanced neuronal networks
NIPS, 2014
Synaptic plasticity in neural networks needs homeostasis with a fast rate detector
PLoS Computational Biology, 2013
Nonnormal amplification in random balanced neuronal networks
Phys. Rev. E, 2012
STDP in adaptive neurons gives close-to-optimal information transmission
Frontiers in Computational Neuroscience, 2010
Code-specific policy gradient learning rules for spiking neurons
NeurIPS, 2009
Preprints
Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations
arXiv, 2021
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability
arXiv, 2018
Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture model
arXiv, 2017
Characterizing variability in nonlinear recurrent neuronal networks
arXiv, 2016