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01/26/2022
Recency Dropout for Recurrent Recommender Systems
Recurrent recommender systems have been successful in capturing the temp...
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10/05/2020
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
Graph-structured data are ubiquitous. However, graphs encode diverse typ...
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02/24/2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows
Normalizing flows transform a simple base distribution into a complex ta...
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02/24/2020
Variational Hyper RNN for Sequence Modeling
In this work, we propose a novel probabilistic sequence model that excel...
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10/18/2019
Point Process Flows
Event sequences can be modeled by temporal point processes (TPPs) to cap...
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02/26/2019
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Recurrent neural networks have gained widespread use in modeling sequent...
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01/25/2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs
Training recurrent neural networks (RNNs) on long sequence tasks is plag...
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10/01/2018
Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos
Inspired by the observation that humans are able to process videos effic...
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07/23/2018
Prediction based on conditional distributions of vine copulas
Vine copula models are a flexible tool in multivariate non-Gaussian dist...
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04/10/2018
Modular Generative Adversarial Networks
Existing methods for multi-domain image-to-image translation (or generat...
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01/25/2018
Generating Handwritten Chinese Characters using CycleGAN
Handwriting of Chinese has long been an important skill in East Asia. Ho...
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10/27/2017
Multi-level Residual Networks from Dynamical Systems View
Deep residual networks (ResNets) and their variants are widely used in m...
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09/12/2017
