AIConfPaper
← Search

Chethan Pandarinath

4 accepted papers

2024

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark

Brianna M. Karpowicz, Joel Ye, Chaofei Fan, Pablo Tostado-Marcos, Fabio Rizzoglio, Clayton B Washington +16
NeurIPS 2024poster

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neura…

Cited by 1Source ↗PDF ↗code ↗Scholar ↗
2021

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time

Feng Zhu, Andrew R Sedler, Harrison A Grier, Nauman Ahad, Mark A. Davenport, Matthew Kaufman +2
NeurIPS 2021poster

Modern neural interfaces allow access to the activity of up to a million neurons within brain circuits. However, bandwidth limits often create a trade-off between greater spatial sampling (more channels or pixels) and the temporal frequency of sampling. Here we demonstrate that it is possible to obt…

Cited by 14Source ↗PDF ↗code ↗Scholar ↗
2021

Neural Latents Benchmark ‘21: Evaluating latent variable models of neural population activity

Felix C Pei, Joel Ye, David M. Zoltowski, Anqi Wu, Raeed Hasan Chowdhury, Hansem Sohn +10
NeurIPS 2021poster

Advances in neural recording present increasing opportunities to study neural activity in unprecedented detail. Latent variable models (LVMs) are promising tools for analyzing this rich activity across diverse neural systems and behaviors, as LVMs do not depend on known relationships between the act…

Cited by 98Source ↗code ↗Scholar ↗
2019

Enabling hyperparameter optimization in sequential autoencoders for spiking neural data

Mohammad Reza Keshtkaran, Chethan Pandarinath
NeurIPS 2019poster

Continuing advances in neural interfaces have enabled simultaneous monitoring of spiking activity from hundreds to thousands of neurons. To interpret these large-scale data, several methods have been proposed to infer latent dynamic structure from high-dimensional datasets. One recent line of work u…

Cited by 51Source ↗PDF ↗code ↗Scholar ↗