Sungsoo Ahn

44 papers · 2015–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (8) 🏃 Academic Marathon (10) 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🤝 Dynamic Duo (15) 👑 Triple Crown 💎 Century Club (44) ⚡ Prolific Year (5) 🔥 Unstoppable (11) ❓ The Questioner 📈 Trend Setter 🗃️ Keyword Collector (129)

Conferences

ICLR (13) ICML (11) NIPS (11) EMNLP (3) ACL (2) IJCAI (2) AISTATS (1) CVPR (1)

Top co-authors

Jinwoo Shin (15) Minsu Kim (8) Yunhui Jang (8) Jinkyoo Park (7) Michael Chertkov (5) Hyosoon Jang (4) Junsu Kim (4) Jaeho Lee (3) Sung-Soo Ahn (3) Hankook Lee (3)

Keywords

variational inference (4) large language model (4) graphical model (3) graph neural network (3) partition function (3) deep neural network (3) belief propagation (3) gauge transformation (2) approximate inference (2) molecular optimization (2) mini-bucket elimination (2) molecular structure (2) spurious correlation (2) combinatorial optimization (2) molecular generation (2) neural network (2) ensemble learning (1) feature learning (1) transfer learning (1) robust optimization (1)

Papers

Adaptive teachers for amortized samplers ICLR 2025

Structural Reasoning Improves Molecular Understanding of LLM ACL 2025

REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring ICLR 2025

Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers ICLR 2025

MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks ICLR 2025

Generative Flows on Synthetic Pathway for Drug Design ICLR 2025

Self-Training Large Language Models with Confident Reasoning EMNLP 2025

MT-Mol: Multi Agent System with Tool-based Reasoning for Molecular Optimization EMNLP 2025

Improving Chemical Understanding of LLMs via SMILES Parsing EMNLP 2025

Enhancing LLM Agent Safety via Causal Influence Prompting ACL 2025

EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost IJCAI 2024

Pessimistic Backward Policy for GFlowNets NIPS 2024

Graph Generation with $K^2$-trees ICLR 2024

A Simple and Scalable Representation for Graph Generation ICLR 2024

Learning Energy Decompositions for Partial Inference in GFlowNets ICLR 2024

Local Search GFlowNets ICLR 2024

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More ICML 2024

Gaussian Plane-Wave Neural Operator for Electron Density Estimation ICML 2024

Hybrid Neural Representations for Spherical Data ICML 2024

Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization ICML 2024

Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization ICML 2024

Breadth-First Exploration on Adaptive Grid for Reinforcement Learning ICML 2024

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences NIPS 2023

A Closer Look at the Intervention Procedure of Concept Bottleneck Models ICML 2023

Imitating Graph-Based Planning with Goal-Conditioned Policies ICLR 2023

Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion NIPS 2023

Diffusion Probabilistic Models for Structured Node Classification NIPS 2023

Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022

Learning Debiased Classifier with Biased Committee NIPS 2022

What Makes Better Augmentation Strategies? Augment Difficult but Not too Different ICLR 2022

Spanning Tree-based Graph Generation for Molecules ICLR 2022

Self-Improved Retrosynthetic Planning ICML 2021

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning IJCAI 2021

RoMA: Robust Model Adaptation for Offline Model-based Optimization NIPS 2021

Layer-adaptive Sparsity for the Magnitude-based Pruning ICLR 2021

Guiding Deep Molecular Optimization with Genetic Exploration NIPS 2020

Learning from Failure: De-biasing Classifier from Biased Classifier NIPS 2020

Learning What to Defer for Maximum Independent Sets ICML 2020

Variational Information Distillation for Knowledge Transfer CVPR 2019

Bucket Renormalization for Approximate Inference ICML 2018

Gauged Mini-Bucket Elimination for Approximate Inference AISTATS 2018

Gauging Variational Inference NIPS 2017

Synthesis of MCMC and Belief Propagation NIPS 2016

Minimum Weight Perfect Matching via Blossom Belief Propagation NIPS 2015