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08/24/2023
The intersection of video capsule endoscopy and artificial intelligence: addressing unique challenges using machine learning
Introduction: Technical burdens and time-intensive review processes limi...
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05/26/2023
Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought
Language instructions and demonstrations are two natural ways for users ...
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05/23/2023
Provably Learning Object-Centric Representations
Learning structured representations of the visual world in terms of obje...
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08/07/2022
How Adversarial Robustness Transfers from Pre-training to Downstream Tasks
Given the rise of large-scale training regimes, adapting pre-trained mod...
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07/29/2022
Weakly Supervised Deep Instance Nuclei Detection using Points Annotation in 3D Cardiovascular Immunofluorescent Images
Two major causes of death in the United States and worldwide are stroke ...
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07/08/2022
Pixel-level Correspondence for Self-Supervised Learning from Video
While self-supervised learning has enabled effective representation lear...
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06/29/2022
MaNi: Maximizing Mutual Information for Nuclei Cross-Domain Unsupervised Segmentation
In this work, we propose a mutual information (MI) based unsupervised do...
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04/26/2022
Encoding Cardiopulmonary Exercise Testing Time Series as Images for Classification using Convolutional Neural Network
Exercise testing has been available for more than a half-century and is ...
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11/04/2021
Unsupervised Learning of Compositional Energy Concepts
Humans are able to rapidly understand scenes by utilizing concepts extra...
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06/13/2021
HistoTransfer: Understanding Transfer Learning for Histopathology
Advancement in digital pathology and artificial intelligence has enabled...
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06/08/2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Self-supervised representation learning has shown remarkable success in ...
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03/19/2021
Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification
In recent years, the availability of digitized Whole Slide Images (WSIs)...
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02/17/2021
Contrastive Learning Inverts the Data Generating Process
Contrastive learning has recently seen tremendous success in self-superv...
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10/12/2020
Improving Low Resource Code-switched ASR using Augmented Code-switched TTS
Building Automatic Speech Recognition (ASR) systems for code-switched sp...
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07/21/2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
We construct an unsupervised learning model that achieves nonlinear dise...
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07/13/2020
S2RMs: Spatially Structured Recurrent Modules
Capturing the structure of a data-generating process by means of appropr...
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06/12/2020
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences
Perceiving the world in terms of objects is a crucial prerequisite for r...
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05/23/2020
Devising Malware Characterstics using Transformers
With the increasing number of cybersecurity threats, it becomes more dif...
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02/28/2019
On the Effectiveness of Low Frequency Perturbations
Carefully crafted, often imperceptible, adversarial perturbations have b...
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12/06/2018
Max-Margin Adversarial (MMA) Training: Direct Input Space Margin Maximization through Adversarial Training
We propose Max-Margin Adversarial (MMA) training for directly maximizing...
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09/29/2018
CAAD 2018: Generating Transferable Adversarial Examples
Deep neural networks (DNNs) are vulnerable to adversarial examples, pert...
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05/28/2018
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization
Deep neural networks (DNNs) are vulnerable to adversarial examples, even...
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04/21/2018
Generating Natural Language Adversarial Examples
Deep neural networks (DNNs) are vulnerable to adversarial examples, pert...
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03/27/2018
Bypassing Feature Squeezing by Increasing Adversary Strength
Feature Squeezing is a recently proposed defense method which reduces th...
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10/30/2017
Attacking the Madry Defense Model with L_1-based Adversarial Examples
The Madry Lab recently hosted a competition designed to test the robustn...
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09/13/2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Recent studies have highlighted the vulnerability of deep neural network...
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08/14/2017
