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ORCIDMikail Khona
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2020 – today
- 2024
[c7]Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka:
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. ICML 2024- [c6]Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka:
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks. ICML 2024 - [i11]Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka:
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. CoRR abs/2402.07757 (2024) - [i10]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:
Bridging Associative Memory and Probabilistic Modeling. CoRR abs/2402.10202 (2024) - [i9]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:
Large language models surpass human experts in predicting neuroscience results. CoRR abs/2403.03230 (2024) - [i8]Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo:
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. CoRR abs/2406.09366 (2024) - [i7]Rylan Schaeffer, Mikail Khona, Sanmi Koyejo:
In-Context Learning of Energy Functions. CoRR abs/2406.12785 (2024) - [i6]Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R. Fiete:
Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models. CoRR abs/2406.14549 (2024) - [i5]Kento Nishi, Maya Okawa, Rahul Ramesh, Mikail Khona, Ekdeep Singh Lubana, Hidenori Tanaka:
Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing. CoRR abs/2410.17194 (2024) - 2023
- [j1]Mikail Khona, Sarthak Chandra, Joy J. Ma, Ila R. Fiete:
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs. Neural Comput. 35(11): 1850-1869 (2023) - [c5]Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Fiete:
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. NeurIPS 2023 - [i4]Rylan Schaeffer, Mikail Khona, Zachary Robertson, Akhilan Boopathy, Kateryna Pistunova, Jason W. Rocks, Ila Rani Fiete, Oluwasanmi Koyejo:
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. CoRR abs/2303.14151 (2023) - [i3]Ziming Liu, Mikail Khona, Ila R. Fiete, Max Tegmark:
Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks. CoRR abs/2310.07711 (2023) - [i2]Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Rani Fiete:
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. CoRR abs/2311.02316 (2023) - [i1]Rahul Ramesh, Mikail Khona, Robert P. Dick, Hidenori Tanaka, Ekdeep Singh Lubana:
How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks. CoRR abs/2311.12997 (2023) - 2022
- [c4]Sunny Duan, Mikail Khona, Adrian Bertagnoli, Sarthak Chandra, Ila Fiete:
See and Copy: Generation of complex compositional movements from modular and geometric RNN representations. NeurReps 2022: 388-400 - [c3]Rylan Schaeffer, Mikail Khona, Ila Fiete:
No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit. NeurIPS 2022 - 2021
- [c2]Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete:
Efficient online inference for nonparametric mixture models. UAI 2021: 2072-2081 - 2020
- [c1]Rylan Schaeffer, Mikail Khona, Leenoy Meshulam, International Brain Laboratory, Ila Fiete:
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice. NeurIPS 2020
Coauthor Index
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