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How do we determine whether two or more clothing items are compatible or visually appealing? Part of the answer lies in understanding …
Importance weighted variational inference (Burda et al., 2015) uses multiple i.i.d. samples to have a tighter variational lower bound. …
This paper explores the impact of warnings, audio feedback, and gender on human-robot trust in the context of autonomous driving and …
Allowing humans to interactively train artificial agents to understand language instructions is desirable for both practical and …
Can meta-learning discover generic ways of processing time series (TS) from a diverse dataset so as to greatly improve generalization …
Probability distillation has recently been of interest to deep learning practitioners as it presents a practical solution for sampling …
In this work, we propose a novel formulation of planning which views it as a probabilistic inference problem over future optimal …
Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due to their capability to learn short and …
Numerous models for grounded language understanding have been recently proposed, including (i) generic models that can be easily …
Finding tight bounds on the optimal solution is a critical element of practical solution methods for discrete optimization problems. In …