Papers
Learning Instance-wise Sparsity for Accelerating Deep Models
Chuanjian Liu, Yunhe Wang, Kai Han et al.
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker, Gergo Bohner, Julien Boussard et al.
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting
Longyuan Li, Junchi Yan, Xiaokang Yang et al.
Learning interpretable multi-modal features for alignment with supervised iterative descent
Max Blendowski, Mattias P. Heinrich
Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach
Nicolas Pröllochs, Stefan Feuerriegel, Dirk Neumann
Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields
Yue Zhang, Arti Ramesh
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations
Andrew Spielberg, Allan Zhao, Yuanming Hu et al.
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract)
Pierre Baldi, Peter Sadowski, Zhiqin Lu
Learning Invariant Representations of Social Media Users
Nicholas Andrews, Marcus Bishop
Learning Invariant Representations of Social Media Users
Nicholas Andrews, Marcus Bishop
Learning Invariant Representations with Kernel Warping
Yingyi Ma, Vignesh Ganapathiraman, Xinhua Zhang
Learning Ising Models with Independent Failures
Surbhi Goel, Daniel M. Kane, Adam R. Klivans
Learning Joint 2D-3D Representations for Depth Completion
Yun Chen, Bin Yang, Ming Liang et al.
Learning Joint Gait Representation via Quintuplet Loss Minimization
Kaihao Zhang, Wenhan Luo, Lin Ma et al.
Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets
Reuben Dorent, Wenqi Li, Jinendra Ekanayake et al.
Learning Joint Reconstruction of Hands and Manipulated Objects
Yana Hasson, Gul Varol, Dimitrios Tzionas et al.
Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval
Xiaoyuan Liang, Martin Renqiang Min, Hongyu Guo et al.
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer et al.
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
John P. Lalor, Hao Wu, Hong Yu
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
John P. Lalor, Hao Wu, Hong Yu
Learning Latent Plans from Play
Corey Lynch, Mohi Khansari, Ted Xiao et al.
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
Qitian Wu, Zixuan Zhang, Xiaofeng Gao et al.
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering
Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon et al.
Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming
Caio Corro, Ivan Titov
Learning Lightweight Lane Detection CNNs by Self Attention Distillation
Yuenan Hou, Zheng Ma, Chunxiao Liu et al.