Chethan Pandarinath

According to our database, Chethan Pandarinath authored at least 13 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes.

Jonathan D. McCart, Andrew R. Sedler, Christopher Versteeg, Domenick Mifsud, Mattia Rigotti-Thompson, Chethan Pandarinath

CoRR, 2024

2023

High-performance neural population dynamics modeling enabled by scalable computational infrastructure.

Aashish N. Patel, Andrew R. Sedler, Jingya Huang, Chethan Pandarinath, Vikash Gilja

J. Open Source Softw., March, 2023

lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems.

Andrew R. Sedler, Chethan Pandarinath

CoRR, 2023

2022

Expressive architectures enhance interpretability of dynamics-based neural population models.

Andrew R. Sedler, Christopher Versteeg, Chethan Pandarinath

CoRR, 2022

2021

Representation learning for neural population activity with Neural Data Transformers.

Joel Ye, Chethan Pandarinath

CoRR, 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 T. Kaufman, Andrea Giovannucci, Chethan Pandarinath

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Felix Pei, Joel Ye, David M. Zoltowski, Anqi Wu, Raeed H. Chowdhury, Hansem Sohn, Joseph E. O'Doherty, Krishna V. Shenoy, Matthew T. Kaufman, Mark M. Churchland, Mehrdad Jazayeri, Lee E. Miller, Jonathan W. Pillow, Il Memming Park, Eva L. Dyer, Chethan Pandarinath

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2019

Enabling hyperparameter optimization in sequential autoencoders for spiking neural data.

Mohammad Reza Keshtkaran, Chethan Pandarinath

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Comparison of Intention Estimation Methods for Decoder Calibration in Intracortical Brain-Computer Interfaces.

Francis R. Willett, Brian A. Murphy, Daniel Young, William D. Memberg, Christine H. Blabe, Chethan Pandarinath, Brian Franco, Jad Saab, Benjamin L. Walter, Jennifer A. Sweet, Jonathan P. Miller, Jaimie M. Henderson, Krishna V. Shenoy, John D. Simeral, Beata Jarosiewicz, Leigh R. Hochberg, Robert F. Kirsch, A. Bolu Ajiboye

IEEE Trans. Biomed. Eng., 2018

Feasibility of Automatic Error Detect-and-Undo System in Human Intracortical Brain-Computer Interfaces.

Nir Even-Chen, Sergey D. Stavisky, Chethan Pandarinath, Paul Nuyujukian, Christine H. Blabe, Leigh R. Hochberg, Jaimie M. Henderson, Krishna V. Shenoy

IEEE Trans. Biomed. Eng., 2018

2016

LFADS - Latent Factor Analysis via Dynamical Systems.

David Sussillo, Rafal Józefowicz, L. F. Abbott, Chethan Pandarinath

CoRR, 2016

2013

A system for optically controlling neural circuits with very high spatial and temporal resolution.

Chethan Pandarinath, Eric T. Carlson, Sheila Nirenberg

Proceedings of the 13th IEEE International Conference on BioInformatics and BioEngineering, 2013

2010

A novel mechanism for switching a neural system from one state to another.

Chethan Pandarinath, Illya Bomash, Jonathan D. Victor, Glen T. Prusky, Wayne Tschetter, Sheila Nirenberg

Frontiers Comput. Neurosci., 2010