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04/16/2023
Out-of-Variable Generalization
The ability of an agent to perform well in new and unseen environments i...
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01/31/2023
The passive symmetries of machine learning
Any representation of data involves arbitrary investigator choices. Beca...
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01/27/2023
Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion
The recent surge in popularity of diffusion models for image generation ...
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11/07/2022
FED-CD: Federated Causal Discovery from Interventional and Observational Data
Causal discovery, the inference of causal relations from data, is a core...
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10/12/2022
AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation
To approach the level of advanced human players in table tennis with rob...
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07/22/2022
Discrete Key-Value Bottleneck
Deep neural networks perform well on prediction and classification tasks...
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05/25/2022
Amortized Inference for Causal Structure Learning
Learning causal structure poses a combinatorial search problem that typi...
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02/28/2022
Logical Fallacy Detection
Reasoning is central to human intelligence. However, fallacious argument...
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12/21/2021
On the Adversarial Robustness of Causal Algorithmic Recourse
Algorithmic recourse seeks to provide actionable recommendations for ind...
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10/29/2021
Resampling Base Distributions of Normalizing Flows
Normalizing flows are a popular class of models for approximating probab...
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10/07/2021
Boxhead: A Dataset for Learning Hierarchical Representations
Disentanglement is hypothesized to be beneficial towards a number of dow...
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09/06/2021
Learning Neural Causal Models with Active Interventions
Discovering causal structures from data is a challenging inference probl...
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07/01/2021
Generalization and Robustness Implications in Object-Centric Learning
The idea behind object-centric representation learning is that natural s...
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06/15/2021
Towards Total Recall in Industrial Anomaly Detection
Being able to spot defective parts is a critical component in large-scal...
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02/22/2021
Towards Causal Representation Learning
The two fields of machine learning and graphical causality arose and dev...
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10/13/2020
On the Fairness of Causal Algorithmic Recourse
While many recent works have studied the problem of algorithmic fairness...
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06/14/2020
Structural Autoencoders Improve Representations for Generation and Transfer
We study the problem of structuring a learned representation to signific...
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06/12/2020
Kernel Distributionally Robust Optimization
This paper is an in-depth investigation of using kernel methods to immun...
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11/29/2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
In recent years, the interest in unsupervised learning of disentangled r...
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10/31/2018
Interventional Robustness of Deep Latent Variable Models
The ability to learn disentangled representations that split underlying ...
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07/20/2018
Photorealistic Video Super Resolution
With the advent of perceptual loss functions, new possibilities in super...
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06/04/2018
groupICA: Independent component analysis for grouped data
We introduce groupICA, a novel independent component analysis (ICA) algo...
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08/14/2017
Learning Blind Motion Deblurring
As handheld video cameras are now commonplace and available in every sma...
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12/23/2016
EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis
Single image super-resolution is the task of inferring a high-resolution...
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05/31/2016
