David Wipf

46 papers · 2013–2025 · 7 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (13) 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird

🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (13) 🌟 Keyword Trendsetter Combo (3) 👑 Triple Crown 🔬 Deep Specialist (11) 👥 Mega-Team (20) 🏆 Keyword Champion (2) ⚡ Prolific Year (5) 🔥 Unstoppable (13) 🗃️ Keyword Collector (144) ❓ The Questioner (5) 📈 Trend Setter 💎 Century Club (46) 🚀 Conference Pioneer

Conferences

ICML (15) ICLR (9) ICCV (5) NIPS (5) AISTATS (4) CVPR (4) JMLR (4)

Top co-authors

Quan Gan (8) Zheng Zhang (5) Junchi Yan (5) Tong He (5) Yangkun Wang (5) Minjie Wang (4) Bin Dai (4) Jiaolong Yang (4) Qitian Wu (4) zengfeng Huang (4)

Keywords

graph neural network (7) bayesian inference (5) variational inference (4) latent representation (3) representation learning (3) image restoration (3) message passing (3) sparse estimation (3) blind deconvolution (3) sparse representation (3) variational autoencoder (3) domain adaptation (2) long short-term memory (2) bayesian learning (2) convolutional neural network (2) bilevel optimization (2) energy function (2) non-convex optimization (2) image deblurring (2) generative model (2)

Papers

Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable ICLR 2025 Griffin: Towards a Graph-Centric Relational Database Foundation Model ICML 2025 Sparse Autoencoders, Again? ICML 2025 Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners AISTATS 2025 Common Learning Constraints Alter Interpretations of Direct Preference Optimization AISTATS 2025 Explicit Preference Optimization: No Need for an Implicit Reward Model ICML 2025 Transformers from Diffusion: A Unified Framework for Neural Message Passing JMLR 2025 Implicit vs Unfolded Graph Neural Networks JMLR 2025 MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy ICLR 2025 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs NIPS 2024 How Graph Neural Networks Learn: Lessons from Training Dynamics ICML 2024 Graph Machine Learning through the Lens of Bilevel Optimization AISTATS 2024 Robust Angular Synchronization via Directed Graph Neural Networks ICLR 2024 Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations ICML 2023 From Hypergraph Energy Functions to Hypergraph Neural Networks ICML 2023 DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion ICLR 2023 On the Initialization of Graph Neural Networks ICML 2023 Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features ICLR 2022 GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks ICML 2022 Why Propagate Alone? Parallel Use of Labels and Features on Graphs ICLR 2022 Inductive Relation Prediction Using Analogy Subgraph Embeddings ICLR 2022 Handling Distribution Shifts on Graphs: An Invariance Perspective ICLR 2022 Graph Neural Networks Inspired by Classical Iterative Algorithms ICML 2021 Sparse Multi-Path Corrections in Fringe Projection Profilometry CVPR 2021 Learning Hierarchical Graph Neural Networks for Image Clustering ICCV 2021 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse ICML 2020 Diagnosing and Enhancing VAE Models ICLR 2019 Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements CVPR 2019 Face Video Deblurring Using 3D Facial Priors ICCV 2019 Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models JMLR 2018 Revisiting Deep Intrinsic Image Decompositions CVPR 2018 Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing ICCV 2017 From Bayesian Sparsity to Gated Recurrent Nets NIPS 2017 Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016 Maximal Sparsity with Deep Networks? NIPS 2016 A Pseudo-Bayesian Algorithm for Robust PCA NIPS 2016 Multi-Task Learning for Subspace Segmentation ICML 2015 Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA ICML 2015 Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-Encoders ICCV 2015 Understanding and Evaluating Sparse Linear Discriminant Analysis AISTATS 2015 Revisiting Bayesian Blind Deconvolution JMLR 2014 Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior CVPR 2013 A Practical Transfer Learning Algorithm for Face Verification ICCV 2013 Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse Penalty NIPS 2013 Fixed-Point Model For Structured Labeling ICML 2013