Ole Winther

34 papers · 2005–2024 · 7 conferences · across top CS/AI conferences

Achievements

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🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🗺️ Taxonomy Completionist (15) 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🔬 Deep Specialist (12) 🏆 Keyword Champion 🗃️ Keyword Collector (138) 📈 Trend Setter 💎 Century Club (34) 🔥 Unstoppable (9) ⚡ Prolific Year (6)

Conferences

NIPS (14) ICML (6) JMLR (6) ICLR (4) AISTATS (2) ECCV (1) ICCV (1)

Top co-authors

Ulrich Paquet (6) Andrea Dittadi (5) Anders Christensen (4) Søren Kaae Sønderby (4) Manfred Opper (4) Lars Maaløe (3) Valentin Liévin (3) Francesco Locatello (3) Bernhard Schölkopf (3) Giorgio Giannone (3)

Keywords

variational inference (9) bayesian inference (5) generative model (5) expectation propagation (5) latent variable model (5) variational autoencoder (5) gaussian process (5) approximate inference (3) representation learning (3) normalizing flow (2) bayesian learning (2) diffusion model (2) structure learning (2) spike and slab prior (2) sparse recovery (2) sparse modeling (2) partition function (2) ising model (2) markov chain monte carlo (2) factor model (2)

Papers

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