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On Batch Normalisation for Approximate Bayesian Inference
We study batch normalisation in the context of variational inference met...
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Continual Learning in Low-rank Orthogonal Subspaces
In continual learning (CL), a learner is faced with a sequence of tasks,...
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Diagnosing and Preventing Instabilities in Recurrent Video Processing
Recurrent models are becoming a popular choice for video enhancement tas...
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How benign is benign overfitting?
We investigate two causes for adversarial vulnerability in deep neural n...
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Progressive Skeletonization: Trimming more fat from a network at initialization
Recent studies have shown that skeletonization (pruning parameters) of n...
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A Revised Generative Evaluation of Visual Dialogue
Evaluating Visual Dialogue, the task of answering a sequence of question...
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Calibrating Deep Neural Networks using Focal Loss
Miscalibration – a mismatch between a model's confidence and its correct...
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Using Hindsight to Anchor Past Knowledge in Continual Learning
In continual learning, the learner faces a stream of data whose distribu...
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Mirror Descent View for Neural Network Quantization
Quantizing large Neural Networks (NN) while maintaining the performance ...
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Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh 6:32 PM We propose an interactive GAN-based sketch-to-image ...
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Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Exciting new work on the generalization bounds for neural networks (NN) ...
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Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
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Visual Dialogue without Vision or Dialogue
We characterise some of the quirks and shortcomings in the exploration o...
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Proximal Mean-field for Neural Network Quantization
Compressing large neural networks by quantizing the parameters, while ma...
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Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration
Deformable registration has been one of the pillars of biomedical image ...
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Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
We study the incremental learning problem for the classification task, a...
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Deformable Registration through Learning of Context-Specific Metric Aggregation
We propose a novel weakly supervised discriminative algorithm for learni...
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Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation
We propose an approach to discover class-specific pixels for the weakly-...
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Multi-Agent Diverse Generative Adversarial Networks
This paper describes an intuitive generalization to the Generative Adver...
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Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
In this paper, we propose several improvements on the block-coordinate F...
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Parsimonious Labeling
We propose a new family of discrete energy minimization problems, which ...
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