Siavash Golkar

According to our database, Siavash Golkar authored at least 25 papers between 2018 and 2025.

Collaborative distances:

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

2025

Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning.

Jeff Shen, François Lanusse, Liam Holden Parker, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Nathan Cassereau, Pierre Cornette, Keiya Hirashima, Géraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Miles D. Cranmer, Shirley Ho

CoRR, October, 2025

Joint Embeddings Go Temporal.

Sofiane Ennadir, Siavash Golkar, Leopoldo Sarra

CoRR, September, 2025

What's In Your Field? Mapping Scientific Research with Knowledge Graphs and Large Language Models.

Abhipsha Das, Nicholas Lourie, Siavash Golkar, Mariel Pettee

CoRR, March, 2025

2024

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task.

Siavash Golkar, Alberto Bietti, Mariel Pettee, Michael Eickenberg, Miles D. Cranmer, Keiya Hirashima, Géraud Krawezik, Nicholas Lourie, Michael McCabe, Rudy Morel, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Shirley Ho

CoRR, 2024

Neuronal Temporal Filters as Normal Mode Extractors.

Siavash Golkar, Jules Berman, David Lipshutz, Robert Mihai Haret, Tim Gollisch, Dmitri B. Chklovskii

CoRR, 2024

Multiple Physics Pretraining for Spatiotemporal Surrogate Models.

Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models.

François Lanusse, Liam Holden Parker, Siavash Golkar, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Géraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

Multiple Physics Pretraining for Physical Surrogate Models.

Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

xVal: A Continuous Number Encoding for Large Language Models.

Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles D. Cranmer, Géraud Krawezik, François Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

Reusability report: Prostate cancer stratification with diverse biologically-informed neural architectures.

Christian Pedersen, Tiberiu Tesileanu, Tinghui Wu, Siavash Golkar, Miles D. Cranmer, Zijun Zhang, Shirley Ho

CoRR, 2023

A normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity.

David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii

CoRR, 2023

An Online Algorithm for Contrastive Principal Component Analysis.

Siavash Golkar, David Lipshutz, Tiberiu Tesileanu, Dmitri B. Chklovskii

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Neural Circuits for Dynamics-Based Segmentation of Time Series.

Tiberiu Tesileanu, Siavash Golkar, Samaneh Nasiri, Anirvan M. Sengupta, Dmitri B. Chklovskii

Neural Comput., 2022

Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy.

Siavash Golkar, Tiberiu Tesileanu, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Biological Learning of Irreducible Representations of Commuting Transformations.

Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis.

David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii

Neural Comput., 2021

Neural optimal feedback control with local learning rules.

Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii

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

2020

A biologically plausible neural network for local supervision in cortical microcircuits.

Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii

CoRR, 2020

A biologically plausible neural network for multi-channel Canonical Correlation Analysis.

David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii

CoRR, 2020

A Biologically Plausible Neural Network for Slow Feature Analysis.

David Lipshutz, Charles Windolf, Siavash Golkar, Dmitri B. Chklovskii

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A simple normative network approximates local non-Hebbian learning in the cortex.

Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Emergent Structures and Lifetime Structure Evolution in Artificial Neural Networks.

Siavash Golkar

CoRR, 2019

Task-Driven Data Verification via Gradient Descent.

Siavash Golkar, Kyunghyun Cho

CoRR, 2019

Continual Learning via Neural Pruning.

Siavash Golkar, Michael Kagan, Kyunghyun Cho

CoRR, 2019

2018

Backdrop: Stochastic Backpropagation.

Siavash Golkar, Kyle Cranmer

CoRR, 2018