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08/25/2023
Active learning for fast and slow modeling attacks on Arbiter PUFs
Modeling attacks, in which an adversary uses machine learning techniques...
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02/13/2023
In Search for a Generalizable Method for Source Free Domain Adaptation
Source-free domain adaptation (SFDA) is compelling because it allows ada...
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04/01/2022
Proper Reuse of Image Classification Features Improves Object Detection
A common practice in transfer learning is to initialize the downstream m...
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01/10/2022
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
Transfer-learning methods aim to improve performance in a data-scarce ta...
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08/07/2021
Impact of Aliasing on Generalization in Deep Convolutional Networks
We investigate the impact of aliasing on generalization in Deep Convolut...
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06/25/2021
Domain Conditional Predictors for Domain Adaptation
Learning guarantees often rely on assumptions of i.i.d. data, which will...
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05/14/2021
Learning a Universal Template for Few-shot Dataset Generalization
Few-shot dataset generalization is a challenging variant of the well-stu...
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04/06/2021
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Meta and transfer learning are two successful families of approaches to ...
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03/07/2019
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Few-shot classification refers to learning a classifier for new classes ...
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02/01/2019
The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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12/01/2018
Cross-Modulation Networks for Few-Shot Learning
A family of recent successful approaches to few-shot learning relies on ...
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10/19/2017
Generative Adversarial Networks: An Overview
Generative adversarial networks (GANs) provide a way to learn deep repre...
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09/22/2017
FiLM: Visual Reasoning with a General Conditioning Layer
We introduce a general-purpose conditioning method for neural networks c...
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07/10/2017
Learning Visual Reasoning Without Strong Priors
Achieving artificial visual reasoning - the ability to answer image-rela...
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05/18/2017
Exploring the structure of a real-time, arbitrary neural artistic stylization network
In this paper, we present a method which combines the flexibility of the...
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03/31/2017
Improved Training of Wasserstein GANs
Generative Adversarial Networks (GANs) are powerful generative models, b...
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10/24/2016
A Learned Representation For Artistic Style
The diversity of painting styles represents a rich visual vocabulary for...
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06/02/2016
Adversarially Learned Inference
We introduce the adversarially learned inference (ALI) model, which join...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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03/23/2016
A guide to convolution arithmetic for deep learning
We introduce a guide to help deep learning practitioners understand and ...
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02/09/2016
Discriminative Regularization for Generative Models
We explore the question of whether the representations learned by classi...
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06/01/2015
Blocks and Fuel: Frameworks for deep learning
We introduce two Python frameworks to train neural networks on large dat...
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12/18/2013
On the Challenges of Physical Implementations of RBMs
Restricted Boltzmann machines (RBMs) are powerful machine learning model...
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08/20/2013
