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ORCIDHidenori Tanaka
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2020 – today
- 2024
[j7]Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie
, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins:
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. Neural Comput. 36(1): 151-174 (2024)- [c18]Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman:
In-Context Learning Dynamics with Random Binary Sequences. ICLR 2024 - [c17]Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Scott Krueger:
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. ICLR 2024 - [c16]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 - [c15]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 - [i15]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) - [i14]Core Francisco Park, Maya Okawa, Andrew Lee, Ekdeep Singh Lubana, Hidenori Tanaka:
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. CoRR abs/2406.19370 (2024) - [i13]Ekdeep Singh Lubana, Kyogo Kawaguchi, Robert P. Dick, Hidenori Tanaka:
A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language. CoRR abs/2408.12578 (2024) - 2023
- [c14]Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self supervised learning? ICLR 2023 - [c13]Ekdeep Singh Lubana, Eric J. Bigelow, Robert P. Dick, David Scott Krueger, Hidenori Tanaka:
Mechanistic Mode Connectivity. ICML 2023: 22965-23004 - [c12]Fatih Dinc, Adam Shai, Mark Schnitzer, Hidenori Tanaka:
CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics. NeurIPS 2023 - [c11]Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. NeurIPS 2023 - [i12]Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. CoRR abs/2310.09336 (2023) - [i11]Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman:
In-Context Learning Dynamics with Random Binary Sequences. CoRR abs/2310.17639 (2023) - [i10]Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Edward Grefenstette, Tim Rocktäschel, David Scott Krueger:
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. CoRR abs/2311.12786 (2023) - [i9]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
- [j6]Gautam Reddy, Laura Desban, Hidenori Tanaka, Julian Roussel, Olivier Mirat, Claire Wyart:
A lexical approach for identifying behavioural action sequences. PLoS Comput. Biol. 18(1) (2022) - [i8]Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self-supervised learning? CoRR abs/2210.00638 (2022) - [i7]Ekdeep Singh Lubana, Eric J. Bigelow, Robert P. Dick, David Scott Krueger, Hidenori Tanaka:
Mechanistic Mode Connectivity. CoRR abs/2211.08422 (2022) - 2021
- [j5]Hidenori Tanaka, Jason F. Kreisberg, Trey Ideker:
Genetic dissection of complex traits using hierarchical biological knowledge. PLoS Comput. Biol. 17(9) (2021) - [c10]Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka:
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. ICLR 2021 - [c9]Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning. NeurIPS 2021: 4778-4791 - [c8]Hidenori Tanaka, Daniel Kunin:
Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks. NeurIPS 2021: 25646-25660 - [i6]Hidenori Tanaka, Daniel Kunin:
Noether's Learning Dynamics: The Role of Kinetic Symmetry Breaking in Deep Learning. CoRR abs/2105.02716 (2021) - [i5]Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning. CoRR abs/2106.05956 (2021) - [i4]Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins:
Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion. CoRR abs/2107.09133 (2021) - 2020
- [c7]Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli:
Pruning neural networks without any data by iteratively conserving synaptic flow. NeurIPS 2020 - [i3]Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli:
Pruning neural networks without any data by iteratively conserving synaptic flow. CoRR abs/2006.05467 (2020) - [i2]Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka:
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. CoRR abs/2012.04728 (2020)
2010 – 2019
- 2019
- [c6]Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen Baccus, Surya Ganguli:
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction. NeurIPS 2019: 8535-8545 - [i1]Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen A. Baccus, Surya Ganguli:
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction. CoRR abs/1912.06207 (2019) - 2010
- [j4]Koichiro Sawa, Takahiro Ueno, Hidenori Tanaka:
A Study on Wear of Brush and Carbon Flat Commutator of DC Motor for Automotive Fuel Pump. IEICE Trans. Electron. 93-C(9): 1443-1448 (2010) - [j3]Xinping Wang, Tomomasa Nagashima, Kentarou Fukuta, Yoshifumi Okada, Masahiro Sawai, Hidenori Tanaka, Takashi Uozumi:
Statistical method for classifying cries of baby based on pattern recognition of power spectrum. Int. J. Biom. 2(2): 113-123 (2010)
2000 – 2009
- 2009
- [j2]Tetsuro Yabu, Hidenori Tanaka, Masaharu Ohashi:
Simple Model for Estimating Birefringence of LPFG Using Photoelastic Effect. IEICE Trans. Electron. 92-C(6): 887-889 (2009) - [c5]Hidenori Tanaka, Hideo Saito:
Dynamics Analysis of Facial Expressions for Person Identification. CAIP 2009: 107-115 - 2008
- [j1]Tomomasa Nagashima, Hidenori Tanaka, Takashi Uozumi:
An overview of Kansei engineering: a proposal of Kansei informatics toward realising safety and pleasantness of individuals in information network society. Int. J. Biom. 1(1): 3-19 (2008) - [c4]Kyoko Sudo, Tatsuya Osawa, Hidenori Tanaka, Hideki Koike, Kenichi Arakawa:
Online anomal movement detection based on unsupervised incremental learning. ICPR 2008: 1-4 - 2007
- [c3]Hidenori Tanaka, Atsushi Nakazawa, Haruo Takemura:
Human Pose Estimation from Volume Data and Topological Graph Database. ACCV (1) 2007: 618-627 - 2005
- [c2]Hidenori Tanaka, Itaru Kitahara, Hideo Saito, Hiroshi Murase, Kiyoshi Kogure, Norihiro Hagita:
Dynamically Visual Learning for People Identification with Sparsely Distributed Cameras. SCIA 2005: 130-140
1990 – 1999
- 1992
- [c1]Shozo Kondo, Tong Xu, Hidenori Tanaka, Manas Sangwarasil, Kiyoaki Atsuta:
Shape and source from shading using zero crossings. ICPR (1) 1992: 534-537
Coauthor Index
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