Neural Machine Translation with Latent Semantic of Image and Text. - Joji Toyama; Masanori Misono; Masahiro Suzuki 001; Kotaro Nakayama; Yutaka Matsuo (CoRR, 2016)

Joint Multimodal Learning with Deep Generative Models. - Masahiro Suzuki 001; Kotaro Nakayama; Yutaka Matsuo (ICLR (Workshop), 2017)

Improving Bi-directional Generation between Different Modalities with Variational Autoencoders. - Masahiro Suzuki 001; Kotaro Nakayama; Yutaka Matsuo (CoRR, 2018)

UVTON: UV Mapping to Consider the 3D Structure of a Human in Image-Based Virtual Try-On Network. - Shizuma Kubo; Yusuke Iwasawa; Masahiro Suzuki 001; Yutaka Matsuo (ICCV Workshops, 2019)

Dual Space Learning with variational Autoencoders. - Hirono Okamoto; Masahiro Suzuki 001; Itto Higuchi; Shohei Ohsawa; Yutaka Matsuo (DGS@ICLR, 2019)

Pixyz: a library for developing deep generative models. - Masahiro Suzuki 001; Takaaki Kaneko; Yutaka Matsuo (CoRR, 2021)

A survey of multimodal deep generative models. - Masahiro Suzuki 001; Yutaka Matsuo (Adv. Robotics, 2022)

Fixing the Train-test Objective Discrepancy: Iterative Image Inpainting for Unsupervised Anomaly Detection. - Hitoshi Nakanishi; Masahiro Suzuki 001; Yutaka Matsuo (J. Inf. Process., 2022)

Interaction-Based Disentanglement of Entities for Object-Centric World Models. - Akihiro Nakano; Masahiro Suzuki 001; Yutaka Matsuo (ICLR, 2023)

End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization. - Shohei Taniguchi; Masahiro Suzuki 001; Yusuke Iwasawa; Yutaka Matsuo (ICML, 2023)

Improving the Robustness to Variations of Objects and Instructions with a Neuro-Symbolic Approach for Interactive Instruction Following. - Kazutoshi Shinoda; Yuki Takezawa; Masahiro Suzuki 001; Yusuke Iwasawa; Yutaka Matsuo (MMM (2), 2023)

HAWK-Net: Hierarchical Attention Weighted Top-K Network for High-resolution Image Classification. - Hitoshi Nakanishi; Masahiro Suzuki 001; Yutaka Matsuo (J. Inf. Process., 2023)

Learning global spatial information for multi-view object-centric models. - Yuya Kobayashi; Masahiro Suzuki 001; Yutaka Matsuo (Adv. Robotics, 2023)

Pixyz: a Python library for developing deep generative models. - Masahiro Suzuki 001; Takaaki Kaneko; Yutaka Matsuo (Adv. Robotics, 2023)

ADOPT: Modified Adam Can Converge with Any β2 with the Optimal Rate. - Shohei Taniguchi; Keno Harada; Gouki Minegishi; Yuta Oshima; Seong Cheol Jeong; Go Nagahara; Tomoshi Iiyama; Masahiro Suzuki 001; Yusuke Iwasawa; Yutaka Matsuo (NeurIPS, 2024)

SSM Meets Video Diffusion Models: Efficient Video Generation with Structured State Spaces. - Yuta Oshima; Shohei Taniguchi; Masahiro Suzuki 001; Yutaka Matsuo (CoRR, 2024)

The Embodied World Model Based on LLM with Visual Information and Prediction-Oriented Prompts. - Wakana Haijima; Kou Nakakubo; Masahiro Suzuki 001; Yutaka Matsuo (CoRR, 2024)

Enhancing Unimodal Latent Representations in Multimodal VAEs through Iterative Amortized Inference. - Yuta Oshima; Masahiro Suzuki 001; Yutaka Matsuo (CoRR, 2024)

Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases. - Cristian Meo; Akihiro Nakano; Mircea Lica; Aniket Didolkar; Masahiro Suzuki 001; Anirudh Goyal; Mengmi Zhang; Justin Dauwels; Yutaka Matsuo; Yoshua Bengio (CoRR, 2024)

The Geometry of Phase Transitions in Diffusion Models: Tubular Neighbourhoods and Singularities. - Manato Yaguchi; Kotaro Sakamoto; Ryosuke Sakamoto; Masato Tanabe; Masatomo Akagawa; Yusuke Hayashi; Masahiro Suzuki 001; Yutaka Matsuo (Trans. Mach. Learn. Res., 2025)

Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search. - Yuta Oshima; Masahiro Suzuki 001; Yutaka Matsuo; Hiroki Furuta (CoRR, 2025)

How Semantically Informative is an Image?: Measuring the Covariance-Weighted Norm of Contrastive Learning Embeddings. - Fumiya Uchiyama; Rintaro Yanagi; Shohei Taniguchi; Shota Takashiro; Masahiro Suzuki 001; Hirokatsu Kataoka; Yusuke Iwasawa; Yutaka Matsuo (CoRR, 2025)