Welling, Max
Max Welling investigador
Welling, Max, 1968-
VIAF ID: 198411906 (Personal)
Permalink: http://viaf.org/viaf/198411906
Preferred Forms
- 100 0 _ ‡a Max Welling ‡c investigador
-
-
- 100 1 _ ‡a Welling, Max
- 100 1 _ ‡a Welling, Max
- 100 1 _ ‡a Welling, Max
-
4xx's: Alternate Name Forms (11)
Works
Title | Sources |
---|---|
3D scattering transforms for disease classification in neuroimaging. | |
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data | |
Accelerated Variational Dirichlet Process Mixtures | |
Asynchronous Distributed Learning of Topic Models | |
Bayesian Bits: Unifying Quantization and Pruning | |
Bayesian Compression for Deep Learning | |
Bayesian dark knowledge | |
Bayesian k-Means as a "maximization-expectation" algorithm | |
Bayesian Model Scoring in Markov Random Fields | |
Causal Effect Inference with Deep Latent-Variable Models | |
Classical and quantum gravity in 2+1 dimensions | |
Combinatorial Bayesian Optimization using the Graph Cartesian Product | |
Combining Generative and Discriminative Models for Hybrid Inference | |
Computer Vision - ECCV 2016 : 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I | |
Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation | |
The Convolution Exponential and Generalized Sylvester Flows | |
Deep Scale-spaces: Equivariance Over Scale | |
Distributed Inference for Latent Dirichlet Allocation | |
Editor's Note | |
Experimental design for MRI by greedy policy search | |
Exponential Family Harmoniums with an Application to Information Retrieval | |
The Functional Neural Process | |
Geluidsmetingen op het Stationsplein in Leiden | |
Improved Variational Inference with Inverse Autoregressive Flow | |
Infinite State Bayes-Nets for Structured Domains | |
Integer Discrete Flows and Lossless Compression | |
An introduction to variational autoencoders, 2019: | |
Invert to Learn to Invert | |
Learning Sparse Topographic Representations with Products of Student-t Distributions | |
Linear response algorithms for approximate inference in graphical models. | |
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning | |
Natural Graph Networks | |
On Herding and the Perceptron Cycling Theorem | |
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference | |
Over leven met kunstmatige intelligentie | |
POPE: post optimization posterior evaluation of likelihood free models | |
Positive tensor factorization | |
Predicting Simulation Parameters of Biological Systems Using a Gaussian Process Model | |
Probabilistic sequential independent components analysis | |
Products of "Edge-perts" | |
Recurrent inference machines for reconstructing heterogeneous MRI data | |
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks | |
Self Supervised Boosting | |
Semi-Supervised Classification with Graph Convolutional Networks | |
Semi-supervised learning with deep generative models | |
Sequential Tests for Large-Scale Learning | |
Spherical CNNs | |
Statistical Tests for Optimization Efficiency | |
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows | |
Tænker computere bedre uden hjælp? | |
The Time-Marginalized Coalescent Prior for Hierarchical Clustering | |
Topographic product models applied to natural scene statistics. | |
The Unified Propagation and Scaling Algorithm | |
Unsupervised discovery of nonlinear structure using contrastive backpropagation | |
Unsupervised organization of image collections: taxonomies and beyond. | |
Variational Dropout and the Local Reparameterization Trick | |
Wormholes Improve Contrastive Divergence |