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Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers

Mar 27, 2021
Tianyu Zhu, Markus Hiller, Mahsa Ehsanpour, Rongkai Ma, Tom Drummond, Hamid Rezatofighi

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Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features

Jun 10, 2021
Thomas M. McDonald, Mauricio A. Álvarez

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Learning Hamiltonian dynamics by reservoir computer

Apr 24, 2021
Han Zhang, Huawei Fan, Liang Wang, Xingang Wang

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Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression

Jul 04, 2021
Grzegorz Dudek

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Learning to Act Safely with Limited Exposure and Almost Sure Certainty

May 25, 2021
Agustin Castellano, Hancheng Min, Juan Bazerque, Enrique Mallada

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Visual Representation Learning Does Not Generalize Strongly Within the Same Domain

Jul 23, 2021
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel

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PocketVAE: A Two-step Model for Groove Generation and Control

Jul 11, 2021
Kyungyun Lee, Wonil Kim, Juhan Nam

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RotLSTM: Rotating Memories in Recurrent Neural Networks

May 01, 2021
Vlad Velici, Adam Prügel-Bennett

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Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms

May 20, 2021
Xiaocheng Tang, Fan Zhang, Zhiwei Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye

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A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models

Apr 08, 2020
Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica T Davis, Alessandro Vespignani, Mauricio Santillana

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