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Understanding Deep Generative Models with Generalized Empirical Likelihoods
Understanding how well a deep generative model captures a distribution of high-dimensional data remains an important open challenge. It …
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Queer In AI: A Case Study in Community-Led Participatory AI
We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and …
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Deep Grasp Adaptation through Domain Transfer
Learning-based methods for robotic grasping have been shown to yield high performance. However, they rely on expensive-to-acquire and …
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Optimal Transport for Offline Imitation Learning
With the advent of large datasets, offline reinforcement learning is a promising framework for learning good decision-making policies …
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Actually Sparse Variational Gaussian Processes
A typical criticism of Gaussian processes is their unfavourable scaling in both compute and memory requirements. Sparse variational …
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Transfer and zero-shot learning for weed species detection with small datasets and unseen classes
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Actually Sparse Variational Gaussian Processes
In this work, we propose a new class of inter-domain variational Gaussian process, constructed by projecting onto a set of compactly …
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Optimal Transport for Offline Imitation Learning
With the advent of large datasets, offline reinforcement learning is a promising framework for learning good decision-making policies …
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Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes
Short-term forecasting of solar photovoltaic energy (PV) production is important for powerplant management. Ideally these forecasts are …
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One-Shot Transfer of Affordance Regions? AffCorrs!
In this work, we tackle one-shot visual search of object parts. Given a single reference image of an object with annotated affordance …
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One-Shot Transfer of Affordance Regions? AffCorrs!