
Bayesian Reasoning with DeepLearned Knowledge
We access the internalized understanding of trained, deep neural network...
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Causality for Machine Learning
Graphical causal inference as pioneered by Judea Pearl arose from resear...
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Representation Learning for OutOfDistribution Generalization in Reinforcement Learning
Learning data representations that are useful for various downstream tas...
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Towards Causal Representation Learning
The two fields of machine learning and graphical causality arose and dev...
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Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
We study the problem of causal discovery through targeted interventions....
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Neural Monocular 3D Human Motion Capture with Physical Awareness
We present a new trainable system for physically plausible markerless 3D...
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MultiGarment Net: Learning to Dress 3D People from Images
We present MultiGarment Network (MGN), a method to predict body shape a...
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Learning Dynamical Systems using Local Stability Priors
A coupled computational approach to simultaneously learn a vector field ...
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GRAF: Generative Radiance Fields for 3DAware Image Synthesis
While 2D generative adversarial networks have enabled highresolution im...
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Convolutional neural networks: a magic bullet for gravitationalwave detection?
In the last few years, machine learning techniques, in particular convol...
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From Variational to Deterministic Autoencoders
Variational Autoencoders (VAEs) provide a theoreticallybacked framework...
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PRINCE: Providerside Interpretability with Counterfactual Explanations in Recommender Systems
Interpretable explanations for recommender systems and other machine lea...
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360Degree Textures of People in Clothing from a Single Image
In this paper we predict a full 3D avatar of a person from a single imag...
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Predicting Landscapes from Environmental Conditions Using Generative Networks
Landscapes are meaningful ecological units that strongly depend on the e...
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VideoForensicsHQ: Detecting Highquality Manipulated Face Videos
New approaches to synthesize and manipulate face videos at very high qua...
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Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
In recent years, Generative Adversarial Networks have achieved impressiv...
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A Computational Model of Early Word Learning from the Infant's Point of View
Human infants have the remarkable ability to learn the associations betw...
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STANCY: Stance Classification Based on Consistency Cues
Controversial claims are abundant in online media and discussion forums....
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NRST: Nonrigid Surface Tracking from Monocular Video
We propose an efficient method for nonrigid surface tracking from monoc...
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Differentiation of Blackbox Combinatorial Solvers
Achieving fusion of deep learning with combinatorial algorithms promises...
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Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations
The goal of many computer vision systems is to transform image pixels in...
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A New DistributionFree Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming
This work presents the concept of kernel mean embedding and kernel proba...
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Neural Body Fitting: Unifying Deep Learning and ModelBased Human Pose and Shape Estimation
Direct prediction of 3D body pose and shape remains a challenge even for...
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Interventional Robustness of Deep Latent Variable Models
The ability to learn disentangled representations that split underlying ...
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Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture
This paper addresses the problem of interpolating visual textures. We fo...
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We Are Not Your Real Parents: Telling Causal from Confounded using MDL
Given data over variables (X_1,...,X_m, Y) we consider the problem of fi...
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Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing
Despite significant success in Visual Question Answering (VQA), VQA mode...
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Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
Building on recent progress at the intersection of combinatorial optimiz...
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Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data
The utility of aerial imagery (Satellite, Drones) has become an invaluab...
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Is Independence all you need? On the Generalization of Representations Learned from Correlated Data
Despite impressive progress in the last decade, it still remains an open...
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STAR: Sparse Trained Articulated Human Body Regressor
The SMPL body model is widely used for the estimation, synthesis, and an...
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Learning Graph Embeddings for Compositional Zeroshot Learning
In compositional zeroshot learning, the goal is to recognize unseen com...
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BackwardCompatible Prediction Updates: A Probabilistic Approach
When machine learning systems meet real world applications, accuracy is ...
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Neuron ranking  an informed way to condense convolutional neural networks architecture
Convolutional neural networks (CNNs) in recent years have made a dramati...
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ParameterFree Spatial Attention Network for Person ReIdentification
Global average pooling (GAP) allows to localize discriminative informati...
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AReS and MaRS  Adversarial and MMDMinimizing Regression for SDEs
Stochastic differential equations are an important modeling class in man...
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Planning from Images with Deep Latent Gaussian Process Dynamics
Planning is a powerful approach to control problems with known environme...
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Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms
The reliable fraction of information is an attractive score for quantify...
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MetaTransfer Learning for FewShot Learning
Metalearning has been proposed as a framework to address the challengin...
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Deconfounding Reinforcement Learning in Observational Settings
We propose a general formulation for addressing reinforcement learning (...
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ODIN: ODEInformed Regression for Parameter and State Inference in TimeContinuous Dynamical Systems
Parameter inference in ordinary differential equations is an important p...
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A Novel BiLevel Paradigm for ImagetoImage Translation
Imagetoimage (I2I) translation is a pixellevel mapping that requires ...
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CounQER: A System for Discovering and Linking Count Information in Knowledge Bases
Predicate constraints of generalpurpose knowledge bases (KBs) like Wiki...
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Path Integral Based Convolution and Pooling for Graph Neural Networks
Graph neural networks (GNNs) extends the functionality of traditional ne...
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SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
We present SCANimate, an endtoend trainable framework that takes raw 3...
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UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for MultiView Reconstruction
Neural implicit 3D representations have emerged as a powerful paradigm f...
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Consequential Ranking Algorithms and Longterm Welfare
Ranking models are typically designed to provide rankings that optimize ...
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Deep Nonlinear NonGaussian Filtering for Dynamical Systems
Filtering is a general name for inferring the states of a dynamical syst...
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Taking a Deeper Look at the Inverse Compositional Algorithm
In this paper, we provide a modern synthesis of the classic inverse comp...
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Testing Conditional Independence on Discrete Data using Stochastic Complexity
Testing for conditional independence is a core aspect of constraintbase...
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Max Planck Society
The Max Planck Society for the Advancement of Science is a formally independent nongovernmental and nonprofit association of German research institutes founded in 1911 as the Kaiser Wilhelm Society and renamed the Max Planck Society in 1948 in honor ...