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09/20/2023
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding
While most modern video understanding models operate on short-range clip...
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08/31/2023
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
We present Belebele, a multiple-choice machine reading comprehension (MR...
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07/23/2021
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series
Irregularly sampled time series commonly occur in several domains where ...
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01/25/2021
Multi-Time Attention Networks for Irregularly Sampled Time Series
Irregular sampling occurs in many time series modeling applications wher...
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11/30/2020
A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance
Irregularly sampled time series data arise naturally in many application...
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10/08/2020
Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks
We study the problem of generating adversarial examples in a black-box s...
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07/13/2020
Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
We focus on the problem of black-box adversarial attacks, where the aim ...
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03/24/2020
Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction
Intensive Care Unit Electronic Health Records (ICU EHRs) store multimoda...
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02/07/2020
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification
In this paper, we consider the problem of assessing the adversarial robu...
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09/30/2019
Black-box Adversarial Attacks with Bayesian Optimization
We focus on the problem of black-box adversarial attacks, where the aim ...
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09/13/2019
Interpolation-Prediction Networks for Irregularly Sampled Time Series
In this paper, we present a new deep learning architecture for addressin...
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12/03/2018