Barnabás Póczos

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