research
∙
04/19/2023
Investigating the Nature of 3D Generalization in Deep Neural Networks
Visual object recognition systems need to generalize from a set of 2D tr...
share
research
∙
02/03/2023
Blockwise Self-Supervised Learning at Scale
Current state-of-the-art deep networks are all powered by backpropagatio...
research
∙
11/27/2022
Domain Generalization for Robust Model-Based Offline Reinforcement Learning
Existing offline reinforcement learning (RL) algorithms typically assume...
research
∙
09/20/2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics
Modern machine learning research relies on relatively few carefully cura...
research
∙
06/13/2022
Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification
It is generally believed that the human visual system is biased towards ...
research
∙
03/03/2022
Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training
Health mentioning classification (HMC) classifies an input text as healt...
research
∙
07/10/2021
Identifying Layers Susceptible to Adversarial Attacks
Common neural network architectures are susceptible to attack by adversa...
research
∙
08/30/2020
Benchmarking adversarial attacks and defenses for time-series data
The adversarial vulnerability of deep networks has spurred the interest ...
research
∙
05/28/2020
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
With the advancement of powerful image processing and machine learning t...
research
∙
05/05/2020
Interpreting Deep Models through the Lens of Data
Identification of input data points relevant for the classifier (i.e. se...
research
∙
04/06/2020
TSInsight: A local-global attribution framework for interpretability in time-series data
With the rise in the employment of deep learning methods in safety-criti...
research
∙
05/15/2019
TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features
Neural networks (NN) are considered as black-boxes due to the lack of ex...
research
∙
02/15/2019
KINN: Incorporating Expert Knowledge in Neural Networks
The promise of ANNs to automatically discover and extract useful feature...
research
∙
02/08/2018