Joohwan Ko

According to our database, Joohwan Ko authored at least 12 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Latent Target Score Matching, with an application to Simulation-Based Inference.

Joohwan Ko, Tomas Geffner

CoRR, February, 2026

2025

Relaxed Sequence Sampling for Diverse Protein Design.

Joohwan Ko, Aristofanis Rontogiannis, Yih-En Andrew Ban, Axel Elaldi, Nicholas T. Franklin

CoRR, October, 2025

Model Informed Flows for Bayesian Inference of Probabilistic Programs.

Joohwan Ko, Justin Domke

CoRR, May, 2025

Learnable Orthogonal Decomposition for Non-Regressive Prediction for PDE.

Yun Young Choi, Kyujin Han, Joohwan Ko, Sangwook Baek, Seunghwan Lee

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

A Gated MLP Architecture for Learning Topological Dependencies in Spatio-Temporal Graphs.

Yun Young Choi, Minho Lee, Sun Woo Park, Seunghwan Lee, Joohwan Ko

CoRR, 2024

Layer-Adaptive State Pruning for Deep State Space Models.

Minseon Gwak, Seongrok Moon, Joohwan Ko, PooGyeon Park

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Enhancing Topological Dependencies in Spatio-Temporal Graphs With Cycle Message Passing Blocks.

Minho Lee, Yun Young Choi, Sun Woo Park, Seunghwan Lee, Joohwan Ko, Jaeyoung Hong

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

Provably Scalable Black-Box Variational Inference with Structured Variational Families.

Joohwan Ko, Kyurae Kim, Woochang Kim, Jacob R. Gardner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning to Scale Logits for Temperature-Conditional GFlowNets.

Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Demystifying SGD with Doubly Stochastic Gradients.

Kyurae Kim, Joohwan Ko, Yian Ma, Jacob R. Gardner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Modeling Choice via Self-Attention.

Joohwan Ko, Andrew A. Li

CoRR, 2023

Learning to Scale Logits for Temperature-Conditional GFlowNets.

Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woochang Kim, Jinkyoo Park, Yoshua Bengio

CoRR, 2023