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Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
However, it is known that even with infinite i.i.d.
Learning Disentangled Representation for Robust Person Re-identification
Neural Information Processing Systems http://nips.cc/
Recurrent Relational Networks
Rasmus Palm, Ulrich Paquet, Ole Winther
As an illustrative example, consider solving a Sudoku.
Learning To Learn Around A Common Mean
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Neural Information Processing Systems http://nips.cc/
Cross-Modal Learning with Adversarial Samples
CHAO LI, Shangqian Gao, Cheng Deng, De Xie, Wei Liu
A novel cross-modal adversarial sample learning algorithm is presented.
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics
Molecular dynamics (MD) is a broadly adopted technique to approximate such quantities.
Learning elementary structures for 3D shape generation and matching
Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir Kim, Bryan Russell, Mathieu Aubry
Weproposetorepresent shapesasthedeformation andcombination oflearnable elementary 3D structures, which are primitives resulting from training over a collection of shapes.
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao, Shiqing Ma, Yingqi Liu, Xiangyu Zhang
Adversarial sample attacks perturb benign inputs to induce DNN misbehaviors. Recent research has demonstrated the widespread presence and the devastating consequences of such attacks.
