Hidenori Tanaka
21 papers · 2019–2025 · 3 venues · across top CS/AI venues
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(12)
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(3)
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(5)
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Machine Learning
(18)
Deep Learning
(12)
Optimization & Theory Β· Machine Learning
(12)
Artificial Intelligence
(11)
Core AI
(10)
Architectures
(6)
Core Methods
(6)
Optimization & Theory Β· Deep Learning
(5)
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(4)
Natural Language Processing
(3)
Models
(3)
Interdisciplinary
(2)
Cognitive Science
(2)
Resources & Methods
(2)
Techniques
(2)
Keywords
learning dynamics
(5)
emergent capability
(3)
representation learning
(3)
in-context learning
(3)
compositional generalization
(3)
neural network
(2)
transformer
(2)
deep neural network
(2)
formal language
(2)
concept learning
(2)
neural network optimization
(2)
diffusion model
(2)
loss landscape
(2)
generative model
(2)
batch normalization
(1)
stochastic gradient descent
(1)
knowledge editing
(1)
self-supervised learning
(1)
lottery ticket hypothesis
(1)
neural network pruning
(1)
Papers
A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language
ICLR 2025
Competition Dynamics Shape Algorithmic Phases of In-Context Learning
ICLR 2025
Dynamical phases of short-term memory mechanisms in RNNs
ICML 2025
Forking Paths in Neural Text Generation
ICLR 2025
ICLR: In-Context Learning of Representations
ICLR 2025
Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing
ICML 2025
Swing-by Dynamics in Concept Learning and Compositional Generalization
ICLR 2025
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks
ICML 2024
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space
NeurIPS 2024
In-Context Learning Dynamics with Random Binary Sequences
ICLR 2024
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
ICLR 2024
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model
ICML 2024
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
NeurIPS 2023
CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics
NeurIPS 2023
Mechanistic Mode Connectivity
ICML 2023
What shapes the loss landscape of self supervised learning?
ICLR 2023
Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning
NeurIPS 2021
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
ICLR 2021
Noetherβs Learning Dynamics: Role of Symmetry Breaking in Neural Networks
NeurIPS 2021
Pruning neural networks without any data by iteratively conserving synaptic flow
NeurIPS 2020
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
NeurIPS 2019