← Authors

Barnabás Póczos

86 papers · 2007–2025 · 14 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (14) 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (28) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (18) 🏠 Conference Loyalist (22) 🌟 Keyword Trendsetter Combo (8) 🤝 Dynamic Duo (24) 👑 Triple Crown 🧬 Topic Evolution 🏆 Keyword Champion (3) 🏆 Grand Slam 🔬 Deep Specialist (14) 🗃️ Keyword Collector (91) 📈 Trend Setter 🔥 Unstoppable (13) 🚀 Conference Pioneer 💎 Century Club (86) ⚡ Prolific Year (13)

Conferences

NIPS (22) AISTATS (21) ICML (16) ICLR (5) JMLR (4) AAAI (3) EMNLP (3) ACL (2) CVPR (2) IJCAI (2) NAACL (2) UAI (2) ICCV (1) INTERSPEECH (1)

Top co-authors

Jeff Schneider (24) Kirthevasan Kandasamy (14) Aarti Singh (9) Shashank Singh (9) Chun-Liang Li (9) Larry Wasserman (6) Ruslan Salakhutdinov (6) Junier Oliva (6) Willie Neiswanger (5) Siamak Ravanbakhsh (5)

Research topics

Probability (3) Statistics (1)

Keywords

nonparametric estimation (10) density estimation (9) bayesian optimization (7) regret bound (6) distribution regression (6) kernel methods (6) convergence rate (5) mutual information (5) divergence estimation (4) stochastic optimization (4) entropy estimation (4) maximum mean discrepancy (4) statistical learning (4) optimal transport (4) generative model (4) renyi divergence (4) representation learning (4) variance reduction (4) learning theory (4) gaussian process (4)

Papers

Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention ICLR 2025
Chemistry-Inspired Diffusion with Non-Differentiable Guidance ICLR 2025
The student becomes the master: Outperforming GPT3 on Scientific Factual Error Correction EMNLP 2023
Task-Based MoE for Multitask Multilingual Machine Translation EMNLP 2023
Unsupervised program synthesis for images by sampling without replacement UAI 2021
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer NAACL 2021
Re-TACRED: Addressing Shortcomings of the TACRED Dataset AAAI 2021
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations AISTATS 2020
Efficient Meta Lifelong-Learning with Limited Memory EMNLP 2020
Minimizing FLOPs to Learn Efficient Sparse Representations ICLR 2020
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction NIPS 2020
Robust Density Estimation under Besov IPM Losses NIPS 2020
Contextual Parameter Generation for Knowledge Graph Link Prediction AAAI 2020
Politeness Transfer: A Tag and Generate Approach ACL 2020
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020
Nonlinear ISA with Auxiliary Variables for Learning Speech Representations INTERSPEECH 2020
VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing ICML 2020
Characterizing and Avoiding Negative Transfer CVPR 2019
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities AAAI 2019
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses NIPS 2019
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations UAI 2019
Competence-based Curriculum Learning for Neural Machine Translation NAACL 2019
Kernel Change-point Detection with Auxiliary Deep Generative Models ICLR 2019
Gradient Descent Provably Optimizes Over-parameterized Neural Networks ICLR 2019
LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds CVPR 2019
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels NIPS 2019
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent AISTATS 2019
Implicit Kernel Learning AISTATS 2019
Learning Local Search Heuristics for Boolean Satisfiability NIPS 2019
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018
Parallelised Bayesian Optimisation via Thompson Sampling AISTATS 2018
A Generic Approach for Escaping Saddle points AISTATS 2018
Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis ACL 2018
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning AISTATS 2018
Transformation Autoregressive Networks ICML 2018
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima ICML 2018
Nonparametric Density Estimation under Adversarial Losses NIPS 2018
The Statistical Recurrent Unit ICML 2017
One Network to Solve Them All -- Solving Linear Inverse Problems Using Deep Projection Models ICCV 2017
Equivariance Through Parameter-Sharing ICML 2017
Nonparanormal Information Estimation ICML 2017
Hypothesis Transfer Learning via Transformation Functions NIPS 2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network NIPS 2017
Deep Sets NIPS 2017
Gradient Descent Can Take Exponential Time to Escape Saddle Points NIPS 2017
Data-driven Random Fourier Features using Stein Effect IJCAI 2017
Multi-fidelity Bayesian Optimisation with Continuous Approximations ICML 2017
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems IJCAI 2016
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization NIPS 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016
Efficient Nonparametric Smoothness Estimation NIPS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models AISTATS 2016
Bayesian Nonparametric Kernel-Learning AISTATS 2016
Stochastic Variance Reduction for Nonconvex Optimization ICML 2016
Boolean Matrix Factorization and Noisy Completion via Message Passing ICML 2016
Estimating Cosmological Parameters from the Dark Matter Distribution ICML 2016
Learning Theory for Distribution Regression JMLR 2016
On Estimating L_2^2 Divergence AISTATS 2015
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants NIPS 2015
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations NIPS 2015
High Dimensional Bayesian Optimisation and Bandits via Additive Models ICML 2015
Two-stage sampled learning theory on distributions AISTATS 2015
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives AISTATS 2015
Fast Function to Function Regression AISTATS 2015
Nonparametric Estimation of Renyi Divergence and Friends ICML 2014
Exponential Concentration of a Density Functional Estimator NIPS 2014
An Analysis of Active Learning with Uniform Feature Noise AISTATS 2014
FuSSO: Functional Shrinkage and Selection Operator AISTATS 2014
Fast Distribution To Real Regression AISTATS 2014
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation ICML 2014
Scale Invariant Conditional Dependence Measures ICML 2013
Distribution to Distribution Regression ICML 2013
Distribution-Free Distribution Regression AISTATS 2013
Nonparametric Estimation of Conditional Information and Divergences AISTATS 2012
Group Anomaly Detection using Flexible Genre Models NIPS 2011
Hierarchical Probabilistic Models for Group Anomaly Detection AISTATS 2011
On the Estimation of $\alpha$-Divergences AISTATS 2011
REGO: Rank-based Estimation of Renyi Information using Euclidean Graph Optimization AISTATS 2010
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs NIPS 2010
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques JMLR 2009
Undercomplete Blind Subspace Deconvolution JMLR 2007