Khona, Mikail

29 publications

ICML 2025 Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing Kento Nishi, Rahul Ramesh, Maya Okawa, Mikail Khona, Hidenori Tanaka, Ekdeep Singh Lubana

ICLR 2025 Uncovering Latent Memories in Large Language Models Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R Fiete

ICML 2024 Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka

NeurIPSW 2024 Does Maximizing Neural Regression Scores Teach Us About the Brain? Rylan Schaeffer, Mikail Khona, Sarthak Chandra, Mitchell Ostrow, Brando Miranda, Sanmi Koyejo

ICMLW 2024 In-Context Learning of Energy Functions Rylan Schaeffer, Mikail Khona, Sanmi Koyejo

NeurIPSW 2024 Position: Maximizing Neural Regression Scores May Not Identify Good Models of the Brain Rylan Schaeffer, Mikail Khona, Sarthak Chandra, Mitchell Ostrow, Brando Miranda, Sanmi Koyejo

ICLRW 2024 Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Dhruv Bhandarkar Pai, Andres Carranza, Victor Lecomte, Alyssa Unell, Mikail Khona, Thomas Edward Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo

ICML 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

ICMLW 2024 Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R Fiete

ICMLW 2024 Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R Fiete

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Victor Lecomte, Mikail Khona, Yann LeCun, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Victor Lecomte, Rylan Schaeffer, Berivan Isik, Mikail Khona, Yann LeCun, Sanmi Koyejo, Andrey Gromov, Ravid Shwartz-Ziv

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Berivan Isik, Victor Lecomte, Rylan Schaeffer, Yann LeCun, Mikail Khona, Ravid Shwartz-Ziv, Sanmi Koyejo, Andrey Gromov

NeurIPSW 2023 Associative Memory Under the Probabilistic Lens: Improved Transformers & Dynamic Memory Creation Rylan Schaeffer, Mikail Khona, Nika Zahedi, Ila R Fiete, Andrey Gromov, Sanmi Koyejo

NeurIPSW 2023 Divergence at the Interpolation Threshold: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle Rylan Schaeffer, Zachary Robertson, Akhilan Boopathy, Mikail Khona, Ila Fiete, Andrey Gromov, Sanmi Koyejo

NeurIPSW 2023 Growing Brains in Recurrent Neural Networks for Multiple Cognitive Tasks Ziming Liu, Mikail Khona, Ila Fiete, Max Tegmark

NeurIPSW 2023 Growing Brains: Co-Emergence of Anatomical and Functional Modularity in Recurrent Neural Networks Ziming Liu, Mikail Khona, Ila R Fiete, Max Tegmark

NeurIPSW 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

NeurIPSW 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

NeurIPS 2023 Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristobal Eyzaguirre, Sanmi Koyejo, Ila Fiete

NeurIPSW 2023 Stepwise Inference in Transformers: Exploring a Synthetic Graph Navigation Task Mikail Khona, Maya Okawa, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka

NeurIPSW 2023 Testing Assumptions Underlying a Unified Theory for the Origin of Grid Cells Rylan Schaeffer, Mikail Khona, Adrian Bertagnoli, Sanmi Koyejo, Ila R Fiete

NeurIPSW 2023 Testing Assumptions Underlying a Unified Theory for the Origin of Grid Cells Rylan Schaeffer, Mikail Khona, Adrian Bertagnoli, Sanmi Koyejo, Ila Fiete

NeurIPSW 2023 Testing Assumptions Underlying a Unified Theory for the Origin of Grid Cells Rylan Schaeffer, Mikail Khona, Adrian Bertagnoli, Sanmi Koyejo, Ila R Fiete

NeurIPS 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

ICMLW 2022 No Free Lunch from Deep Learning in Neuroscience: A Case Study Through Models of the Entorhinal-Hippocampal Circuit Rylan Schaeffer, Mikail Khona, Ila R Fiete

NeurIPSW 2022 See and Copy: Generation of Complex Compositional Movements from Modular and Geometric RNN Representations Sunny Duan, Mikail Khona, Adrian Bertagnoli, Sarthak Chandra, Ila R Fiete

UAI 2021 Efficient Online Inference for Nonparametric Mixture Models Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete

NeurIPS 2020 Reverse-Engineering Recurrent Neural Network Solutions to a Hierarchical Inference Task for Mice Rylan Schaeffer, Mikail Khona, Leenoy Meshulam, Brain Laboratory International, Ila Fiete