Ole Winther

BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks ICLR 2024 DiffEnc: Variational Diffusion with a Learned Encoder ICLR 2024 Geometry Fidelity for Spherical Images ECCV 2024 Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation NeurIPS 2023 Image-Free Classifier Injection for Zero-Shot Classification ICCV 2023 Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics NeurIPS 2023 Unifying Molecular and Textual Representations via Multi-task Language Modelling ICML 2023 Variational Open-Domain Question Answering ICML 2023 Generalization and Robustness Implications in Object-Centric Learning ICML 2022 SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation ICML 2022 The Role of Pretrained Representations for the OOD Generalization of RL Agents ICLR 2022 On the Transfer of Disentangled Representations in Realistic Settings ICLR 2021 Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow NeurIPS 2020 Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds NeurIPS 2020 SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows NeurIPS 2020 BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling NeurIPS 2019 Bayesian Structure Learning for Dynamic Brain Connectivity AISTATS 2018 Recurrent Relational Networks NeurIPS 2018 A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning NeurIPS 2017 Bayesian Inference for Spatio-temporal Spike-and-Slab Priors JMLR 2017 Hash Embeddings for Efficient Word Representations NeurIPS 2017 Autoencoding beyond pixels using a learned similarity metric ICML 2016 Auxiliary Deep Generative Models ICML 2016 Bayesian Generalised Ensemble Markov Chain Monte Carlo AISTATS 2016 Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models JMLR 2016 Ladder Variational Autoencoders NeurIPS 2016 Sequential Neural Models with Stochastic Layers NeurIPS 2016 Bayesian Inference for Structured Spike and Slab Priors NeurIPS 2014 Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models JMLR 2013 Sparse Linear Identifiable Multivariate Modeling JMLR 2011 Bayesian Sparse Factor Models and DAGs Inference and Comparison NeurIPS 2009 Perturbation Corrections in Approximate Inference: Mixture Modelling Applications JMLR 2009 Improving on Expectation Propagation NeurIPS 2008 Expectation Consistent Approximate Inference JMLR 2005 Semi-Supervised Mean Fields AISTATS 1999