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Tomohiro Hayase
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2020 – today
- 2024
- [c6]Tomohiro Hayase, Ryo Karakida:
Understanding MLP-Mixer as a wide and sparse MLP. ICML 2024 - [i9]Tomohiro Hayase, Braun Sacha, Hikari Yanagawa, Itsuki Orito, Yuichi Hiroi:
PanoTree: Autonomous Photo-Spot Explorer in Virtual Reality Scenes. CoRR abs/2405.17136 (2024) - [i8]Michikuni Eguchi, Madoka Ito, Tomohiro Hayase, Yuichi Hiroi, Takefumi Hiraki:
Cluster Haptic Texture Database: Haptic Texture Database with Variety in Velocity and Direction of Sliding Contacts. CoRR abs/2407.16206 (2024) - 2023
- [c5]Ryo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa:
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias. ICML 2023: 15809-15827 - [i7]Tomohiro Hayase, Ryo Karakida:
MLP-Mixer as a Wide and Sparse MLP. CoRR abs/2306.01470 (2023) - 2022
- [c4]Tomohiro Hayase, Suguru Yasutomi, Nakamasa Inoue:
Downstream Augmentation Generation For Contrastive Learning. ICASSP 2022: 2115-2119 - [i6]Ryo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa:
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias. CoRR abs/2210.02720 (2022) - 2021
- [c3]Tomohiro Hayase
, Ryo Karakida:
The Spectrum of Fisher Information of Deep Networks Achieving Dynamical Isometry. AISTATS 2021: 334-342 - [c2]Shohei Kubota, Hideaki Hayashi
, Tomohiro Hayase, Seiichi Uchida:
Layer-Wise Interpretation of Deep Neural Networks using Identity Initialization. ICASSP 2021: 3945-3949 - [c1]Takefumi Hiraki, Tomohiro Hayase, Yuichi Ike, Takashi Tsuboi, Michio Yoshiwaki:
Viewpoint Planning of Projector Placement for Spatial Augmented Reality using Star-Kernel Decomposition. VR Workshops 2021: 583-584 - [i5]Shohei Kubota, Hideaki Hayashi, Tomohiro Hayase, Seiichi Uchida:
Layer-Wise Interpretation of Deep Neural Networks Using Identity Initialization. CoRR abs/2102.13333 (2021) - [i4]Benoit Collins
, Tomohiro Hayase:
Asymptotic Freeness of Layerwise Jacobians Caused by Invariance of Multilayer Perceptron: The Haar Orthogonal Case. CoRR abs/2103.13466 (2021) - 2020
- [i3]Tomohiro Hayase, Ryo Karakida:
The Spectrum of Fisher Information of Deep Networks Achieving Dynamical Isometry. CoRR abs/2006.07814 (2020) - [i2]Tomohiro Hayase, Suguru Yasutomi, Takashi Katoh:
Selective Forgetting of Deep Networks at a Finer Level than Samples. CoRR abs/2012.11849 (2020)
2010 – 2019
- 2018
- [i1]Tomohiro Hayase:
Cauchy noise loss for stochastic optimization of random matrix models via free deterministic equivalents. CoRR abs/1804.03154 (2018)
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