Joohwan Ko

According to our database, Joohwan Ko authored at least 9 papers between 2023 and 2025.

Collaborative distances:

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

2025

Model Informed Flows for Bayesian Inference of Probabilistic Programs.

Joohwan Ko, Justin Domke

CoRR, May, 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 38: 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