A novel on-off algorithm for smart antenna system operating in IMT2000 mobile communications. - Zhengzi Li; Sungsoo Ahn; Seungwon Choi (VTC Fall, 2001)

Performance Analysis of a Antenna Array System Using a New Beamforming Algorithm in the CDMA2000 1X Wireless Communication. - Sungsoo Ahn; Minsoo Kim; Jungsuk Lee; Dong-Young Lee (KES (2), 2005)

On-Off Beamforming Algorithm Based on Eigen-Space Method for a Smart Antenna in IS-2000 1X Signal Environments. - Zhengzi Li; Weon-Cheol Lee; Sungsoo Ahn; Seungwon Choi (IEICE Trans. Commun., 2005)

Performance Analysis Using the Two Kinds of Receiving Gain of Smart Antenna in IS20001X System. - Sungsoo Ahn; Minsoo Kim; Jungsuk Lee (ICCSA (5), 2006)

Design of CIC roll-off compensation filter in a W-CDMA digital IF receiver. - Seongdo Kim; Weon-Cheol Lee; Sungsoo Ahn; Seungwon Choi (Digit. Signal Process., 2006)

Performance Analysis of MIMO System Utilizing the Detection Algorithm. - Sungsoo Ahn; Dong-Young Lee (ICCSA (4), 2011)

A Study on Hierarchical Policy Model for Managing Heterogeneous Security Systems. - Dong-Young Lee; Sungsoo Ahn; Minsoo Kim (ICCSA (4), 2011)

Effective DDoS attack defense scheme using web service performance measurement. - Namkyun Baik; Sungsoo Ahn; Namhi Kang (ICUFN, 2012)

Minimum Weight Perfect Matching via Blossom Belief Propagation. - Sungsoo Ahn; Sejun Park; Michael Chertkov; Jinwoo Shin (NIPS, 2015)

Synthesis of MCMC and Belief Propagation. - Sungsoo Ahn; Michael Chertkov; Jinwoo Shin (NIPS, 2016)

MCMC assisted by Belief Propagaion. - Sungsoo Ahn; Michael Chertkov; Jinwoo Shin (CoRR, 2016)

Gauging Variational Inference. - Sungsoo Ahn; Michael Chertkov; Jinwoo Shin (NIPS, 2017)

Gauged Mini-Bucket Elimination for Approximate Inference. - Sungsoo Ahn; Michael Chertkov; Jinwoo Shin; Adrian Weller (AISTATS, 2018)

Bucket Renormalization for Approximate Inference. - Sungsoo Ahn; Michael Chertkov; Adrian Weller; Jinwoo Shin (ICML, 2018)

Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality. - Sungsoo Ahn; Michael Chertkov; Andrew E. Gelfand; Sejun Park; Jinwoo Shin (IEEE Trans. Inf. Theory, 2018)

Variational Information Distillation for Knowledge Transfer. - Sungsoo Ahn; Shell Xu Hu; Andreas C. Damianou; Neil D. Lawrence; Zhenwen Dai (CVPR, 2019)

Learning What to Defer for Maximum Independent Sets. - Sungsoo Ahn; Younggyo Seo; Jinwoo Shin (ICML, 2020)

Differentiation of Recurrent Glioblastoma from Radiation Necrosis Using Diffusion Radiomics: Machine Learning Model Development and External Validation. - Yae Won Park; Ji Eun Park; Sungsoo Ahn; Hwiyoung Kim; Ho Sung Kim; Seung-Koo Lee (MLCN/RNO-AI@MICCAI, 2020)

Guiding Deep Molecular Optimization with Genetic Exploration. - Sungsoo Ahn; Junsu Kim; Hankook Lee; Jinwoo Shin (NeurIPS, 2020)

Learning from Failure: De-biasing Classifier from Biased Classifier. - Jun Hyun Nam; Hyuntak Cha; Sungsoo Ahn; Jaeho Lee 001; Jinwoo Shin (NeurIPS, 2020)

QOPT: Optimistic Value Function Decentralization for Cooperative Multi-Agent Reinforcement Learning. - Kyunghwan Son; Sungsoo Ahn; Roben Delos Reyes; Jinwoo Shin; Yung Yi (CoRR, 2020)

Learning from Failure: Training Debiased Classifier from Biased Classifier. - Jun Hyun Nam; Hyuntak Cha; Sungsoo Ahn; Jaeho Lee 001; Jinwoo Shin (CoRR, 2020)

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (CoRR, 2020)

Layer-adaptive Sparsity for the Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (ICLR, 2021)

Self-Improved Retrosynthetic Planning. - Junsu Kim; Sungsoo Ahn; Hankook Lee; Jinwoo Shin (ICML, 2021)

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning. - Hankook Lee; Sungsoo Ahn; Seung-Woo Seo; You Young Song; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (IJCAI, 2021)

RoMA: Robust Model Adaptation for Offline Model-based Optimization. - Sihyun Yu; Sungsoo Ahn; Le Song; Jinwoo Shin (NeurIPS, 2021)

Abstract Reasoning via Logic-guided Generation. - Sihyun Yu; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (CoRR, 2021)

Spanning Tree-based Graph Generation for Molecules. - Sungsoo Ahn; Binghong Chen; Tianzhe Wang; Le Song (ICLR, 2022)

What Makes Better Augmentation Strategies? Augment Difficult but Not too Different. - Jaehyung Kim 001; Dongyeop Kang; Sungsoo Ahn; Jinwoo Shin (ICLR, 2022)

Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning. - Kyunghwan Son; Junsu Kim; Sungsoo Ahn; Roben Delos Reyes; Yung Yi; Jinwoo Shin (ICML, 2022)

Learning Debiased Classifier with Biased Committee. - Nayeong Kim; Sehyun Hwang; Sungsoo Ahn; Jaesik Park; Suha Kwak (NeurIPS, 2022)

Substructure-Atom Cross Attention for Molecular Representation Learning. - Jiye Kim; Seungbeom Lee; Dongwoo Kim 002; Sungsoo Ahn; Jaesik Park (CoRR, 2022)

Imitating Graph-Based Planning with Goal-Conditioned Policies. - Junsu Kim; Younggyo Seo; Sungsoo Ahn; Kyunghwan Son; Jinwoo Shin (ICLR, 2023)

A Closer Look at the Intervention Procedure of Concept Bottleneck Models. - Sungbin Shin; Yohan Jo; Sungsoo Ahn; Namhoon Lee (ICML, 2023)

Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion. - Hyuna Cho; Minjae Jeong; Sooyeon Jeon; Sungsoo Ahn; Won Hwa Kim (NeurIPS, 2023)

Diffusion Probabilistic Models for Structured Node Classification. - Hyosoon Jang; Seonghyun Park 004; Sangwoo Mo; Sungsoo Ahn (NeurIPS, 2023)

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences. - Minsu Kim 004; Federico Berto; Sungsoo Ahn; Jinkyoo Park (NeurIPS, 2023)

Diffusion Probabilistic Models for Graph-Structured Prediction. - Hyosoon Jang; Sangwoo Mo; Sungsoo Ahn (CoRR, 2023)

Hierarchical Graph Generation with K2-trees. - Yunhui Jang; Dongwoo Kim 002; Sungsoo Ahn (CoRR, 2023)

Symmetric Exploration in Combinatorial Optimization is Free! - Hyeonah Kim; Minsu Kim 004; Sungsoo Ahn; Jinkyoo Park (CoRR, 2023)

Triplet Edge Attention for Algorithmic Reasoning. - Yeonjoon Jung; Sungsoo Ahn (CoRR, 2023)

Learning Energy Decompositions for Partial Inference in GFlowNets. - Hyosoon Jang; Minsu Kim; Sungsoo Ahn (ICLR, 2024)

Graph Generation with K2-trees. - Yunhui Jang; Dongwoo Kim 002; Sungsoo Ahn (ICLR, 2024)

A Simple and Scalable Representation for Graph Generation. - Yunhui Jang; Seul Lee; Sungsoo Ahn (ICLR, 2024)

Local Search GFlowNets. - Minsu Kim 004; Taeyoung Yun; Emmanuel Bengio; Dinghuai Zhang; Yoshua Bengio; Sungsoo Ahn; Jinkyoo Park (ICLR, 2024)

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More. - Fanchen Bu; Hyeonsoo Jo; Soo Yong Lee; Sungsoo Ahn; Kijung Shin (ICML, 2024)

Gaussian Plane-Wave Neural Operator for Electron Density Estimation. - Seongsu Kim; Sungsoo Ahn (ICML, 2024)

Hybrid Neural Representations for Spherical Data. - Hyomin Kim; Yunhui Jang; Jaeho Lee 001; Sungsoo Ahn (ICML, 2024)

Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization. - Nayeong Kim; Juwon Kang; Sungsoo Ahn; Jungseul Ok; Suha Kwak (ICML, 2024)

Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization. - Hyeonah Kim; Minsu Kim 004; Sungsoo Ahn; Jinkyoo Park (ICML, 2024)

Breadth-First Exploration on Adaptive Grid for Reinforcement Learning. - Youngsik Yoon; Gangbok Lee; Sungsoo Ahn; Jungseul Ok (ICML, 2024)

EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost. - Jaeseung Heo; Seungbeom Lee; Sungsoo Ahn; Dongwoo Kim 002 (IJCAI, 2024)

Pessimistic Backward Policy for GFlowNets. - Hyosoon Jang; Yunhui Jang; Minsu Kim 004; Jinkyoo Park; Sungsoo Ahn (NeurIPS, 2024)

Controllable Text-to-Image Synthesis for Multi-Modality MR Images. - Kyuri Kim; Yoonho Na; Sung-Joon Ye; Jimin Lee; Sungsoo Ahn; Ji Eun Park; Hwiyoung Kim (WACV, 2024)

Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability. - Yae Won Park; Sujeong Eom; Seungwoo Kim; Sungbin Lim; Ji Eun Park; Ho Sung Kim; Seng Chan You; Sungsoo Ahn; Seung-Koo Lee (Comput. Methods Programs Biomed., 2024)

Collective Variable Free Transition Path Sampling with Generative Flow Network. - Kiyoung Seong; Seonghyun Park 004; Seonghwan Kim 004; Woo Youn Kim; Sungsoo Ahn (CoRR, 2024)

Iterated Energy-based Flow Matching for Sampling from Boltzmann Densities. - Dongyeop Woo; Sungsoo Ahn (CoRR, 2024)

Can LLMs Generate Diverse Molecules? Towards Alignment with Structural Diversity. - Hyosoon Jang; Yunhui Jang; Jaehyung Kim; Sungsoo Ahn (CoRR, 2024)

Chain-of-Thoughts for Molecular Understanding. - Yunhui Jang; Jaehyung Kim; Sungsoo Ahn (CoRR, 2024)

REBIND: Enhancing ground-state molecular conformation via force-based graph rewiring. - Taewon Kim; Hyunjin Seo; Sungsoo Ahn; Eunho Yang (CoRR, 2024)

Non-backtracking Graph Neural Networks. - Seonghyun Park 004; Narae Ryu; Gahee Kim; Dongyeop Woo; Se-Young Yun; Sungsoo Ahn (Trans. Mach. Learn. Res., 2024)

Holistic Molecular Representation Learning via Multi-view Fragmentation. - Seojin Kim; Jaehyun Nam; Junsu Kim; Hankook Lee; Sungsoo Ahn; Jinwoo Shin (Trans. Mach. Learn. Res., 2024)

Enhancing LLM Agent Safety via Causal Influence Prompting. - Dongyoon Hahm; Woogyeol Jin; June Suk Choi; Sungsoo Ahn; Kimin Lee (ACL (Findings), 2025)

Structural Reasoning Improves Molecular Understanding of LLM. - Yunhui Jang; Jaehyung Kim; Sungsoo Ahn (ACL (1), 2025)

Examining the Performance of Mamba Tab for Software Defect Prediction. - Saranya Manikandan; Shivani Jadhav; Duksan Ryu; Sungsoo Ahn (BigComp, 2025)

Adaptive teachers for amortized samplers. - Minsu Kim 004; Sanghyeok Choi; Taeyoung Yun; Emmanuel Bengio; Leo Feng; Jarrid Rector-Brooks; Sungsoo Ahn; Jinkyoo Park; Nikolay Malkin; Yoshua Bengio (ICLR, 2025)

MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks. - Nayoung Kim; Seongsu Kim; Minsu Kim 004; Jinkyoo Park; Sungsoo Ahn (ICLR, 2025)

REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring. - Taewon Kim; Hyunjin Seo; Sungsoo Ahn; Eunho Yang (ICLR, 2025)

Generative Flows on Synthetic Pathway for Drug Design. - Seonghwan Seo; Minsu Kim 004; Tony Shen; Martin Ester; Jinkyoo Park; Sungsoo Ahn; Woo Youn Kim (ICLR, 2025)

Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers. - Kiyoung Seong; Seonghyun Park 004; Seonghwan Kim 004; Woo Youn Kim; Sungsoo Ahn (ICLR, 2025)

A tumor inpainting framework for MRI using automated masks based on channel-specific conditions across the volume. - Kyuri Kim; Hyungjoo Cho; Yoonho Na; Sung-Joon Ye; Jimin Lee; Sungsoo Ahn; Ji Eun Park; Hwiyoung Kim (Biomed. Signal Process. Control., 2025)

Interpretable multimodal transformer for prediction of molecular subtypes and grades in adult-type diffuse gliomas. - Yunsu Byeon; Yae Won Park; Soohyun Lee; Doohyun Park; Hyungseob Shin; Kyunghwa Han; Jong Hee Chang; Se Hoon Kim; Seung-Koo Lee; Sungsoo Ahn; Dosik Hwang (npj Digit. Medicine, 2025)

Decoupled Sequence and Structure Generation for Realistic Antibody Design. - Nayoung Kim; Minsu Kim 004; Sungsoo Ahn; Jinkyoo Park (Trans. Mach. Learn. Res., 2025)

Sampling Decisions. - Michael Chertkov; Sungsoo Ahn; Hamidreza Behjoo (CoRR, 2025)

Search-Based Correction of Reasoning Chains for Language Models. - Minsu Kim 004; Jean-Pierre R. Falet; Oliver E. Richardson; Xiaoyin Chen; Moksh Jain; Sungjin Ahn; Sungsoo Ahn; Yoshua Bengio (CoRR, 2025)

Improving Chemical Understanding of LLMs via SMILES Parsing. - Yunhui Jang; Jaehyung Kim; Sungsoo Ahn (CoRR, 2025)

Learning Flexible Forward Trajectories for Masked Molecular Diffusion. - Hyunjin Seo; Taewon Kim; Sihyun Yu; Sungsoo Ahn (CoRR, 2025)

Self-Training Large Language Models with Confident Reasoning. - Hyosoon Jang; Yunhui Jang; Sungjae Lee; Jungseul Ok; Sungsoo Ahn (CoRR, 2025)

Flexible MOF Generation with Torsion-Aware Flow Matching. - Nayoung Kim; Seongsu Kim; Sungsoo Ahn (CoRR, 2025)

High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction. - Seongsu Kim; Nayoung Kim; Dongwoo Kim; Sungsoo Ahn (CoRR, 2025)

On scalable and efficient training of diffusion samplers. - Minkyu Kim; Kiyoung Seong; Dongyeop Woo; Sungsoo Ahn; Minsu Kim (CoRR, 2025)

Energy-based generator matching: A neural sampler for general state space. - Dongyeop Woo; Minsu Kim; Minkyu Kim; Kiyoung Seong; Sungsoo Ahn (CoRR, 2025)

MT-Mol:Multi Agent System with Tool-based Reasoning for Molecular Optimization. - Hyomin Kim; Yunhui Jang; Sungsoo Ahn (CoRR, 2025)

Learning Collective Variables from Time-lagged Generation. - Seonghyun Park 004; Kiyoung Seong; Soojung Yang; Rafael Gómez-Bombarelli; Sungsoo Ahn (CoRR, 2025)

PARROT: An Open Multilingual Radiology Reports Dataset. - Bastien Le Guellec; Kokou Adambounou; Lisa C. Adams; Thibault Agripnidis; Sungsoo Ahn; Radhia Ait Chalal; Tugba Akinci D. Antonoli; Philippe Amouyel; Henrik Andersson; Raphael Bentegeac; Claudio Benzoni; Antonino Andrea Blandino; et al. (CoRR, 2025)