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11/15/2022
Pretraining ECG Data with Adversarial Masking Improves Model Generalizability for Data-Scarce Tasks
Medical datasets often face the problem of data scarcity, as ground trut...
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05/09/2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
Model robustness is vital for the reliable deployment of machine learnin...
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05/08/2022
A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
Artificial Intelligence (AI) is a fast-growing research and development ...
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11/28/2021
ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning
The ability to reason with multiple hierarchical structures is an attrac...
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11/28/2021
FastTrees: Parallel Latent Tree-Induction for Faster Sequence Encoding
Inducing latent tree structures from sequential data is an emerging tren...
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07/07/2021
Deep Extrapolation for Attribute-Enhanced Generation
Attribute extrapolation in sample generation is challenging for deep neu...
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03/07/2021
RNA Alternative Splicing Prediction with Discrete Compositional Energy Network
A single gene can encode for different protein versions through a proces...
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02/17/2021
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n Parameters
Recent works have demonstrated reasonable success of representation lear...
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10/06/2020
Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder
This paper demonstrates a fatal vulnerability in natural language infere...
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09/05/2020
Player Identification in Hockey Broadcast Videos
We present a deep recurrent convolutional neural network (CNN) approach ...
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06/05/2020
CoCon: A Self-Supervised Approach for Controlled Text Generation
Pretrained Transformer-based language models (LMs) display remarkable na...
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12/21/2019
Jacobian Adversarially Regularized Networks for Robustness
Adversarial examples are crafted with imperceptible perturbations with t...
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12/11/2019
What it Thinks is Important is Important: Robustness Transfers through Input Gradients
Adversarial perturbations are imperceptible changes to input pixels that...
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11/19/2019
Poison as a Cure: Detecting Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
Deep learning models have recently shown to be vulnerable to backdoor po...
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09/07/2018
