Kai Nakaishi
(RIKEN)
「Temperature-induced critical phase transition in large language models」

Taro Toyoizumi
(RIKEN)
「Modeling how the brain learns to represent the world」

Takahiro Nishimichi
(Kyoto Sangyo University)
「Emulators in Cosmological Inference Problem」

Yoh-ichi Mototake
(Hitotsubashi University)
「Interpretable AI to assist scientists' insight into large pattern dynamics」

Takuya Isomura
(RIKEN)
「Bayesian mechanics of self-organizing and evolutionary systems」

Atsushi Yamamura
(Stanford University）
「Stochastic Collapse: A Noise-induced Implicit Bias of Stochastic Gradient Descent」

Jun Takahashi
(The University of New Mexico)
「A Semidefinite Programming approach for Quantum Heisenberg Ground States」

Tomoki Fukai
(OIST)
「Graphical information representations in associative memory models」

Makoto Uemura
(Hiroshima University)
「Data Science in Astronomy and Observation of Galactic Transients」

Toshihiro Ota
(Cyber Agent AI Lab)
「Hopfield/Mixer correspondence: towards a better understanding of MetaFormers architecture design」

Liu Ziyin
(The University of Tokyo)
「Understand and analyze deep learning through the lens of symmetry」

Hayata Yamasaki 
(The University of Tokyo)
「Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation」

Akifumi Okuno 
(The Institute of Statistical Mathematics)
「A Greedy and Optimistic Approach to Clustering with a Specified Uncertainty of Covariates」

Keiichi Tamai
(The University of Tokyo)
「Non-equilibrium phase transitions in artificial deep neural networks」

Taro HITOSUGI
(The University of Tokyo)
「Machine learning and robots change the way of our research」

Akio TOMIYA
(IPUT)
「Lattice QCD and Machine learning」

Tomer GALANTI
(Massachusetts Institute of Technology)
「On the Role of Neural Collapse in Transfer Learning」

Kenji HARADA
(Kyoto University)
「Compressing neural networks by tensor networks」

Koji HASHIMOTO
(Kyoto University)
「Deep learning and emergent spacetime」

Kana MORIWAKI
(The University of Tokyo)
「Deep Learning Application for Reconstruction of Large-Scale Structure of the Universe」

Kentaro MINAMI
(Preferred Networks)
「Deep Learning for Financial Applications」

Shinichiro AKIYAMA
(The University of Tokyo)
「Tensor renormalization group approach to quantum fields on a lattice」

Quoc Hoan TRAN
(The University of Tokyo)
「Quantum Reservoir Computing - from Classical to Quantum Time Series Processing」

Ayaka SAKATA
(Institute of Statistical Mathematics)
「Statistical physics for the Bayesian statistical decision: an application to Group Testing」

Syo YAIDA
(Meta AI)
「Effective Theory of Deep Neural Networks」

Shirley HO
(Princeton University)
「Interpreting (some) neural networks with symbolic regression」

Hajime YOSHINO
(Osaka University）
「Design space of a deep neural network - its spatial evolution and robustness」

Masaaki IMAIZUMI
(The University of Tokyo）
「Generalization Analysis of Deep Learning: Implicit Regularization and Over-parameterization」

Lenka Zdeborova
(EPFL)
「Understanding machine learning via exactly solvable models」

Nobuyuki Yoshioka
(The University of Tokyo)
「Encoding many-body quantum physics into neural networks」

Masayuki Ohzeki
(Tohoku University)
「Quantum annealing and its application for practical problems」

Themis Palpanas
(Paris Descartes University）
「Scalable Machine Learning on Large Sequence Collections」

Gentiane Venture
(Tokyo University of Agriculture and Technology)
Vincent Hernandez (Tokyo University of Agriculture and Technology & Surfclean)
「Deep learning for human activity recognition」