← Authors

Seungjin Choi

18 papers · 2009–2022 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (13) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (89) πŸ“ˆ Trend Setter πŸ’Ž Century Club (18) πŸ”₯ Unstoppable (8) πŸš€ Conference Pioneer

Conferences

AISTATS (5) NIPS (4) ICML (3) ACML (2) CVPR (2) IJCAI (1) UAI (1)

Top co-authors

Juho Lee (8) Jungtaek Kim (3) Yoonho Lee (3) Yong-Deok Kim (3) Sunho Park (2) Sung Ju Hwang (1) Lancelot James (1) Eunho Yang (1) Taewoong Jang (1) Minsu Cho (1)

Keywords

bayesian inference (5) variational inference (3) markov chain monte carlo (2) bayesian nonparametric (2) gaussian process (2) hierarchical clustering (2) normalized random measure (2) mixture model (2) few-shot learning (2) posterior inference (2) bayesian nonparametrics (1) anomaly detection (1) transfer learning (1) similarity search (1) dirichlet process (1) representation learning (1) attention mechanism (1) probabilistic modeling (1) collaborative filtering (1) clustering analysis (1)

Papers

Combinatorial Bayesian optimization with random mapping functions to convex polytopes UAI 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization AISTATS 2022
Neural Complexity Measures NIPS 2020
A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure AISTATS 2019
Forward-Backward Generative Adversarial Networks for Anomaly Detection ACML 2019
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks ICML 2019
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace ICML 2018
Bayesian inference on random simple graphs with power law degree distributions ICML 2017
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NIPS 2016
Learning to Select Pre-Trained Deep Representations With Bayesian Evidence Framework CVPR 2016
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models NIPS 2015
Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility AISTATS 2015
Bilinear Random Projections for Locality-Sensitive Binary Codes CVPR 2015
Scalable Variational Bayesian Matrix Factorization with Side Information AISTATS 2014
Incremental Tree-Based Inference with Dependent Normalized Random Measures AISTATS 2014
Hierarchical Bayesian Matrix Factorization with Side Information IJCAI 2013
Hierarchical Gaussian Process Regression ACML 2010
Clustering sequence sets for motif discovery NIPS 2009