Shape and source from shading using zero crossings. - Shozo Kondo; Tong Xu; Hidenori Tanaka; Manas Sangwarasil; Kiyoaki Atsuta (ICPR (1), 1992)

Dynamically Visual Learning for People Identification with Sparsely Distributed Cameras. - Hidenori Tanaka; Itaru Kitahara; Hideo Saito 001; Hiroshi Murase; Kiyoshi Kogure; Norihiro Hagita (SCIA, 2005)

Human Pose Estimation from Volume Data and Topological Graph Database. - Hidenori Tanaka; Atsushi Nakazawa; Haruo Takemura (ACCV (1), 2007)

Online anomal movement detection based on unsupervised incremental learning. - Kyoko Sudo; Tatsuya Osawa; Hidenori Tanaka; Hideki Koike; Kenichi Arakawa (ICPR, 2008)

An overview of Kansei engineering: a proposal of Kansei informatics toward realising safety and pleasantness of individuals in information network society. - Tomomasa Nagashima; Hidenori Tanaka; Takashi Uozumi (Int. J. Biom., 2008)

Dynamics Analysis of Facial Expressions for Person Identification. - Hidenori Tanaka; Hideo Saito 001 (CAIP, 2009)

Simple Model for Estimating Birefringence of LPFG Using Photoelastic Effect. - Tetsuro Yabu; Hidenori Tanaka; Masaharu Ohashi (IEICE Trans. Electron., 2009)

A Study on Wear of Brush and Carbon Flat Commutator of DC Motor for Automotive Fuel Pump. - Koichiro Sawa; Takahiro Ueno; Hidenori Tanaka (IEICE Trans. Electron., 2010)

Statistical method for classifying cries of baby based on pattern recognition of power spectrum. - Xinping Wang; Tomomasa Nagashima; Kentarou Fukuta; Yoshifumi Okada; Masahiro Sawai; Hidenori Tanaka; Takashi Uozumi (Int. J. Biom., 2010)

From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction. - Hidenori Tanaka; Aran Nayebi; Niru Maheswaranathan; Lane McIntosh; Stephen Baccus; Surya Ganguli (NeurIPS, 2019)

Pruning neural networks without any data by iteratively conserving synaptic flow. - Hidenori Tanaka; Daniel Kunin; Daniel L. K. Yamins; Surya Ganguli (NeurIPS, 2020)

Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. - Daniel Kunin; Javier Sagastuy-Breña; Surya Ganguli; Daniel L. K. Yamins; Hidenori Tanaka (ICLR, 2021)

Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning. - Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka (NeurIPS, 2021)

Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks. - Hidenori Tanaka; Daniel Kunin (NeurIPS, 2021)

Noether's Learning Dynamics: The Role of Kinetic Symmetry Breaking in Deep Learning. - Hidenori Tanaka; Daniel Kunin (CoRR, 2021)

Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning. - Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka (CoRR, 2021)

Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion. - Daniel Kunin; Javier Sagastuy-Breña; Lauren E. Gillespie; Eshed Margalit; Hidenori Tanaka; Surya Ganguli; Daniel L. K. Yamins (CoRR, 2021)

Genetic dissection of complex traits using hierarchical biological knowledge. - Hidenori Tanaka; Jason F. Kreisberg; Trey Ideker (PLoS Comput. Biol., 2021)

A lexical approach for identifying behavioural action sequences. - Gautam Reddy; Laura Desban; Hidenori Tanaka; Julian Roussel; Olivier Mirat; Claire Wyart (PLoS Comput. Biol., 2022)

What shapes the loss landscape of self supervised learning? - Liu Ziyin 001; Ekdeep Singh Lubana; Masahito Ueda; Hidenori Tanaka (ICLR, 2023)

Mechanistic Mode Connectivity. - Ekdeep Singh Lubana; Eric J. Bigelow; Robert P. Dick; David Scott Krueger; Hidenori Tanaka (ICML, 2023)

CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics. - Fatih Dinc; Adam Shai; Mark J. Schnitzer; Hidenori Tanaka (NeurIPS, 2023)

Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. - Maya Okawa; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka (NeurIPS, 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)

In-Context Learning Dynamics with Random Binary Sequences. - Eric J. Bigelow; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka; Tomer D. Ullman (ICLR, 2024)

Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. - Samyak Jain; Robert Kirk; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka; Tim Rocktäschel; Edward Grefenstette; David Scott Krueger (ICLR, 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 (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 (ICML, 2024)

Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. - Core Francisco Park; Maya Okawa; Andrew Lee 001; Ekdeep Singh Lubana; Hidenori Tanaka (NeurIPS, 2024)

Dynamics of Concept Learning and Compositional Generalization. - Yongyi Yang; Core Francisco Park; Ekdeep Singh Lubana; Maya Okawa; Wei Hu; Hidenori Tanaka (CoRR, 2024)

Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing. - Kento Nishi; Maya Okawa; Rahul Ramesh; Mikail Khona; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2024)

Continuous-Time Analysis of Adaptive Optimization and Normalization. - Rhys Gould; Hidenori Tanaka (CoRR, 2024)

Competition Dynamics Shape Algorithmic Phases of In-Context Learning. - Core Francisco Park; Ekdeep Singh Lubana; Itamar Pres; Hidenori Tanaka (CoRR, 2024)

The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. - Daniel Kunin; Javier Sagastuy-Breña; Lauren E. Gillespie; Eshed Margalit; Hidenori Tanaka; Surya Ganguli; Daniel L. K. Yamins (Neural Comput., 2024)

Forking Paths in Neural Text Generation. - Eric J. Bigelow; Ari Holtzman; Hidenori Tanaka; Tomer David Ullman (ICLR, 2025)

A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language. - Ekdeep Singh Lubana; Kyogo Kawaguchi; Robert P. Dick; Hidenori Tanaka (ICLR, 2025)

ICLR: In-Context Learning of Representations. - Core Francisco Park; Andrew Lee 001; Ekdeep Singh Lubana; Yongyi Yang; Maya Okawa; Kento Nishi; Martin Wattenberg; Hidenori Tanaka (ICLR, 2025)

Competition Dynamics Shape Algorithmic Phases of In-Context Learning. - Core Francisco Park; Ekdeep Singh Lubana; Hidenori Tanaka (ICLR, 2025)

Swing-by Dynamics in Concept Learning and Compositional Generalization. - Yongyi Yang; Core Francisco Park; Ekdeep Singh Lubana; Maya Okawa; Wei Hu; Hidenori Tanaka (ICLR, 2025)

A multivariate model incorporating subharmonic measurements for evaluating vocal roughness. - Itsuki Kitayama; Kiyohito Hosokawa; Shinobu Iwaki; Misao Yoshida; Akira Miyauchi; Kenji Aruga; Takanari Kawabe; Toshihiro Kishikawa; Hidenori Tanaka; Takeshi Tsuda; Takashi Sato; Yukinori Takenaka; et al. (npj Digit. Medicine, 2025)

A ghost mechanism: An analytical model of abrupt learning. - Fatih Dinc; Ege Çirakman; Yiqi Jiang; Mert Yüksekgönül; Mark J. Schnitzer; Hidenori Tanaka (CoRR, 2025)

New News: System-2 Fine-tuning for Robust Integration of New Knowledge. - Core Francisco Park; Zechen Zhang; Hidenori Tanaka (CoRR, 2025)

CT-OT Flow: Estimating Continuous-Time Dynamics from Discrete Temporal Snapshots. - Keisuke Kawano; Takuro Kutsuna; Naoki Hayashi; Yasushi Esaki; Hidenori Tanaka (CoRR, 2025)

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? - Tian Qin; Core Francisco Park; Mujin Kwun; Aaron Walsman; Eran Malach; Nikhil Anand; Hidenori Tanaka; David Alvarez-Melis (CoRR, 2025)

In-Context Learning Strategies Emerge Rationally. - Daniel Wurgaft; Ekdeep Singh Lubana; Core Francisco Park; Hidenori Tanaka; Gautam Reddy; Noah D. Goodman (CoRR, 2025)

Emergence of Hierarchical Emotion Organization in Large Language Models. - Bo Zhao 028; Maya Okawa; Eric J. Bigelow; Rose Yu; Tomer D. Ullman; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2025)

Provable Low-Frequency Bias of In-Context Learning of Representations. - Yongyi Yang; Hidenori Tanaka; Wei Hu (CoRR, 2025)