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03/10/2023
TSMixer: An all-MLP Architecture for Time Series Forecasting
Real-world time-series datasets are often multivariate with complex dyna...
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06/15/2022
Test-Time Adaptation for Visual Document Understanding
Self-supervised pretraining has been able to produce transferable repres...
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06/05/2022
Interpretable Mixture of Experts for Structured Data
With the growth of machine learning for structured data, the need for re...
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12/19/2019
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
Multi-horizon forecasting problems often contain a complex mix of inputs...
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10/17/2019
On Concept-Based Explanations in Deep Neural Networks
Deep neural networks (DNNs) build high-level intelligence on low-level r...
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10/16/2019
Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost
Active learning (AL) integrates data labeling and model training to mini...
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08/20/2019
TabNet: Attentive Interpretable Tabular Learning
We propose a novel high-performance interpretable deep tabular data lear...
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02/14/2018
Neural Voice Cloning with a Few Samples
Voice cloning is a highly desired feature for personalized speech interf...
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10/20/2017
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
We present Deep Voice 3, a fully-convolutional attention-based neural te...
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10/20/2017
Deep Voice 3: 2000-Speaker Neural Text-to-Speech
We present Deep Voice 3, a fully-convolutional attention-based neural te...
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02/25/2017
