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06/02/2023
Centered Self-Attention Layers
The self-attention mechanism in transformers and the message-passing mec...
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05/24/2023
Reverse Engineering Self-Supervised Learning
Self-supervised learning (SSL) is a powerful tool in machine learning, b...
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03/23/2023
The Probabilistic Stability of Stochastic Gradient Descent
A fundamental open problem in deep learning theory is how to define and ...
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01/11/2023
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions
Multiplication layers are a key component in various influential neural ...
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12/23/2022
Generalization Bounds for Transfer Learning with Pretrained Classifiers
We study the ability of foundation models to learn representations for c...
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02/18/2022
A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks
Deep learning systems have steadily advanced the state of the art in a w...
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12/30/2021
On the Role of Neural Collapse in Transfer Learning
We study the ability of foundation models to learn representations for c...
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10/06/2021
Meta Internal Learning
Internal learning for single-image generation is a framework, where a ge...
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03/22/2021
Intersection Regularization for Extracting Semantic Attributes
We consider the problem of supervised classification, such that the feat...
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04/26/2020
Evaluation Metrics for Conditional Image Generation
We present two new metrics for evaluating generative models in the class...
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03/27/2020
On the Optimization Dynamics of Wide Hypernetworks
Recent results in the theoretical study of deep learning have shown that...
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02/23/2020
A Critical View of the Structural Causal Model
In the univariate case, we show that by comparing the individual complex...
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02/23/2020
Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative
In the context of learning to map an input I to a function h_I:X→R, we c...
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01/15/2020
A Formal Approach to Explainability
We regard explanations as a blending of the input sample and the model's...
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01/14/2020
Unsupervised Learning of the Set of Local Maxima
This paper describes a new form of unsupervised learning, whose input is...
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01/14/2020
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer
We study the problem of learning to map, in an unsupervised way, between...
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08/30/2019
Domain Intersection and Domain Difference
We present a method for recovering the shared content between two visual...
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07/23/2018
Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs
The recent empirical success of cross-domain mapping algorithms, between...
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12/21/2017
Maximally Distant Cross Domain Generators for Estimating Per-Sample Error
While in supervised learning, the validation error is an unbiased estima...
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03/05/2017