← Authors

David Wipf

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

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (7) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (13) 🌟 Keyword Trendsetter Combo (3) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) πŸ‘₯ Mega-Team (20) πŸ† Keyword Champion (2) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (144) ❓ The Questioner (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (46) πŸš€ 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