Ahn, Sungjin

46 publications

NeurIPS 2025 Adaptive Inference-Time Scaling via Cyclic Diffusion Search Gyubin Lee, Bao N Nguyen Truong, Jaesik Yoon, Dongwoo Lee, Minsu Kim, Yoshua Bengio, Sungjin Ahn

NeurIPS 2025 Compositional Monte Carlo Tree Diffusion for Extendable Planning Jaesik Yoon, Hyeonseo Cho, Sungjin Ahn

ICLR 2025 Dreamweaver: Learning Compositional World Models from Pixels Junyeob Baek, Yi-Fu Wu, Gautam Singh, Sungjin Ahn

NeurIPS 2025 Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning Jaesik Yoon, Hyeonseo Cho, Yoshua Bengio, Sungjin Ahn

ICML 2025 Monte Carlo Tree Diffusion for System 2 Planning Jaesik Yoon, Hyeonseo Cho, Doojin Baek, Yoshua Bengio, Sungjin Ahn

ICLR 2025 MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory Junyeong Park, Junmo Cho, Sungjin Ahn

NeurIPSW 2024 Compositional Visual Reasoning with SlotSSMs Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn

ICML 2024 Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming Hany Hamed, Subin Kim, Dongyeong Kim, Jaesik Yoon, Sungjin Ahn

ICLR 2024 Learning to Compose: Improving Object Centric Learning by Injecting Compositionality Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong

ICLR 2024 Neural Language of Thought Models Yi-Fu Wu, Minseung Lee, Sungjin Ahn

ICML 2024 Parallelized Spatiotemporal Slot Binding for Videos Gautam Singh, Yue Wang, Jiawei Yang, Boris Ivanovic, Sungjin Ahn, Marco Pavone, Tong Che

ICML 2024 PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn

ICLR 2024 Simple Hierarchical Planning with Diffusion Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn

NeurIPS 2024 Slot State Space Models Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn

ICLR 2024 Spatially-Aware Transformers for Embodied Agents Junmo Cho, Jaesik Yoon, Sungjin Ahn

ICML 2023 An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning Jaesik Yoon, Yi-Fu Wu, Heechul Bae, Sungjin Ahn

NeurIPS 2023 Facing Off World Model Backbones: RNNs, Transformers, and S4 Fei Deng, Junyeong Park, Sungjin Ahn

NeurIPS 2023 Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models Yeongbin Kim, Gautam Singh, Junyeong Park, Caglar Gulcehre, Sungjin Ahn

ICLR 2023 Neural Systematic Binder Gautam Singh, Yeongbin Kim, Sungjin Ahn

NeurIPSW 2023 Object-Centric Semantic Vector Quantization Yi-Fu Wu, Minseung Lee, Sungjin Ahn

NeurIPSW 2023 Object-Centric Semantic Vector Quantization Yi-Fu Wu, Minseung Lee, Sungjin Ahn

NeurIPS 2023 Object-Centric Slot Diffusion Jindong Jiang, Fei Deng, Gautam Singh, Sungjin Ahn

ICML 2022 DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations Fei Deng, Ingook Jang, Sungjin Ahn

ICLR 2022 Illiterate DALL-E Learns to Compose Gautam Singh, Fei Deng, Sungjin Ahn

NeurIPS 2022 Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos Gautam Singh, Yi-Fu Wu, Sungjin Ahn

NeurIPSW 2021 DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations Fei Deng, Ingook Jang, Sungjin Ahn

ICLR 2021 Generative Scene Graph Networks Fei Deng, Zhuo Zhi, Donghun Lee, Sungjin Ahn

ICML 2021 Generative Video Transformer: Can Objects Be the Words? Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn

JMLR 2021 ROOTS: Object-Centric Representation and Rendering of 3D Scenes Chang Chen, Fei Deng, Sungjin Ahn

ICML 2021 Structured World Belief for Reinforcement Learning in POMDP Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn

NeurIPSW 2021 TransDreamer: Reinforcement Learning with Transformer World Models Chang Chen, Jaesik Yoon, Yi-Fu Wu, Sungjin Ahn

NeurIPS 2020 Generative Neurosymbolic Machines Jindong Jiang, Sungjin Ahn

ICML 2020 Improving Generative Imagination in Object-Centric World Models Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn

ICML 2020 Robustifying Sequential Neural Processes Jaesik Yoon, Gautam Singh, Sungjin Ahn

ICLR 2020 SCALOR: Generative World Models with Scalable Object Representations Jindong Jiang, Sepehr Janghorbani, Gerard de Melo, Sungjin Ahn

ICLR 2020 SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri, Weihao Sun, Gautam Singh, Fei Deng, Jindong Jiang, Sungjin Ahn

NeurIPS 2019 Neural Multisensory Scene Inference Jae Hyun Lim, Pedro O O. Pinheiro, Negar Rostamzadeh, Chris Pal, Sungjin Ahn

NeurIPS 2019 Sequential Neural Processes Gautam Singh, Jaesik Yoon, Youngsung Son, Sungjin Ahn

NeurIPS 2019 Variational Temporal Abstraction Taesup Kim, Sungjin Ahn, Yoshua Bengio

NeurIPS 2018 Bayesian Model-Agnostic Meta-Learning Jaesik Yoon, Taesup Kim, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, Sungjin Ahn

AAAI 2017 Denoising Criterion for Variational Auto-Encoding Framework Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio

ICLR 2017 Hierarchical Multiscale Recurrent Neural Networks Junyoung Chung, Sungjin Ahn, Yoshua Bengio

AISTATS 2016 Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li, Sungjin Ahn, Max Welling

ICML 2014 Distributed Stochastic Gradient MCMC Sungjin Ahn, Babak Shahbaba, Max Welling

AISTATS 2013 Distributed and Adaptive Darting Monte Carlo Through Regenerations Sungjin Ahn, Yutian Chen, Max Welling

ICML 2012 Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring Sungjin Ahn, Anoop Korattikara Balan, Max Welling