Mikail Khona

According to our database, Mikail Khona authored at least 12 papers between 2020 and 2024.

Collaborative distances:

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

2024

Large language models surpass human experts in predicting neuroscience results.

Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K. Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O. Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R. Patil, Pui-Shee Lee, Rui Mata, Nicholas E. Myers, Jennifer K. Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M. Ales, Michael Gaebler, N. Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M. Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C. Love

CoRR, 2024

Bridging Associative Memory and Probabilistic Modeling.

Rylan Schaeffer, Nika Zahedi, Mikail Khona, Dhruv Pai, Sang T. Truong, Yilun Du, Mitchell Ostrow, Sarthak Chandra, Andres Carranza, Ila Rani Fiete, Andrey Gromov, Sanmi Koyejo

CoRR, 2024

Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model.

Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka

CoRR, 2024

2023

Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs.

Mikail Khona, Sarthak Chandra, Joy J. Ma, Ila R. Fiete

Neural Comput., November, 2023

How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks.

Rahul Ramesh, Mikail Khona, Robert P. Dick, Hidenori Tanaka, Ekdeep Singh Lubana

CoRR, 2023

Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks.

Ziming Liu, Mikail Khona, Ila R. Fiete, Max Tegmark

CoRR, 2023

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle.

Rylan Schaeffer, Mikail Khona, Zachary Robertson, Akhilan Boopathy, Kateryna Pistunova, Jason W. Rocks, Ila Rani Fiete, Oluwasanmi Koyejo

CoRR, 2023

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells.

Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Fiete

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit.

Rylan Schaeffer, Mikail Khona, Ila Fiete

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

See and Copy: Generation of complex compositional movements from modular and geometric RNN representations.

Sunny Duan, Mikail Khona, Adrian Bertagnoli, Sarthak Chandra, Ila Fiete

Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

2021

Efficient online inference for nonparametric mixture models.

Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice.

Rylan Schaeffer, Mikail Khona, Leenoy Meshulam, International Brain Laboratory, Ila Fiete

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