
Learning to Discover Novel Visual Categories via Deep Transfer Clustering
We consider the problem of discovering novel object categories in an ima...
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PyTorch: An Imperative Style, HighPerformance Deep Learning Library
Deep learning frameworks have often focused on either usability or speed...
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Selflabelling via simultaneous clustering and representation learning
Combining clustering and representation learning is one of the most prom...
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The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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Deep Coordination Graphs
This paper introduces the deep coordination graph (DCG) for collaborativ...
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A Survey of Reinforcement Learning Informed by Natural Language
To be successful in realworld tasks, Reinforcement Learning (RL) needs ...
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AttentionGAN: Unpaired ImagetoImage Translation using AttentionGuided Generative Adversarial Networks
Stateoftheart methods in the unpaired imagetoimage translation are ...
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Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
Background: The trend towards largescale studies including population i...
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Deep Residual Reinforcement Learning
We revisit residual algorithms in both modelfree and modelbased reinfo...
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Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning
We present GQSAT, a branching heuristic in a Boolean SAT solver trained ...
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SelectFusion: A Generic Framework to Selectively Learn Multisensory Fusion
Autonomous vehicles and mobile robotic systems are typically equipped wi...
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Exploratory Combinatorial Optimization with Reinforcement Learning
Many realworld problems can be reduced to combinatorial optimization on...
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Count, Crop and Recognise: FineGrained Recognition in the Wild
The goal of this paper is to label all the animal individuals present in...
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A Geometric Approach to Obtain a Bird's Eye View from an Image
The objective of this paper is to rectify any monocular image by computi...
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Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning
We use Bayesian convolutional neural networks and a novel generative mod...
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Adjusting for Confounding in Unsupervised Latent Representations of Images
Biological imaging data are often partially confounded or contain unwant...
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The VGG Image Annotator (VIA)
Manual image annotation, such as defining and labelling regions of inter...
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Generalized OffPolicy ActorCritic
We propose a new objective, the counterfactual objective, unifying exist...
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Asymmetric Generative Adversarial Networks for ImagetoImage Translation
Stateoftheart models for unpaired imagetoimage translation with Gen...
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Meta Learning Deep Visual Words for Fast Video Object Segmentation
Meta learning has attracted a lot of attention recently. In this paper, ...
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Learning Sparse Networks Using Targeted Dropout
Neural networks are easier to optimise when they have many more weights ...
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Knowing The What But Not The Where in Bayesian Optimization
Bayesian optimization has demonstrated impressive success in finding the...
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Transflow Learning: Repurposing Flow Models Without Retraining
It is well known that deep generative models have a rich latent space, a...
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Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
Deep learning has been revolutionary for computer vision and semantic se...
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Transfer Learning for Relation Extraction via RelationGated Adversarial Learning
Relation extraction aims to extract relational facts from sentences. Pre...
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Dropout Distillation for Efficiently Estimating Model Confidence
We propose an efficient way to output better calibrated uncertainty scor...
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Loaded DiCE: Trading off Bias and Variance in AnyOrder Score Function Estimators for Reinforcement Learning
Gradientbased methods for optimisation of objectives in stochastic sett...
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SelfVIO: SelfSupervised Deep Monocular VisualInertial Odometry and Depth Estimation
In the last decade, numerous supervised deep learning approaches requiri...
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A Maximum Entropy approach to Massive Graph Spectra
Graph spectral techniques for measuring graph similarity, or for learnin...
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Temporal Fusion Transformers for Interpretable Multihorizon Time Series Forecasting
Multihorizon forecasting problems often contain a complex mix of inputs...
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Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
Deep latent variable models have become a popular model choice due to th...
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A Generative 3D Facial Model by Adversarial Training
We consider datadriven generative models for the 3D face, and focus in ...
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Surprising Effectiveness of FewImage Unsupervised Feature Learning
Stateoftheart methods for unsupervised representation learning can tr...
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Unifying Training and Inference for Panoptic Segmentation
We present an endtoend network to bridge the gap between training and ...
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Augmented Neural ODEs
We show that Neural Ordinary Differential Equations (ODEs) learn represe...
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DAC: The Double ActorCritic Architecture for Learning Options
We reformulate the option framework as two parallel augmented MDPs. Unde...
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Attention Privileged Reinforcement Learning For Domain Transfer
Applying reinforcement learning (RL) to physical systems presents notabl...
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SKD: Unsupervised Keypoint Detecting for Point Clouds using Embedded Saliency Estimation
In this work we present a novel keypoint detector that uses saliency to ...
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Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU
Signatory is a library for calculating signature and logsignature transf...
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SeqSleepNet: EndtoEnd Hierarchical Recurrent Neural Network for SequencetoSequence Automatic Sleep Staging
Automatic sleep staging has been often treated as a simple classificatio...
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Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
Batch Bayesian optimisation (BO) has been successfully applied to hyperp...
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Unsupervised Learning of Landmarks by Descriptor Vector Exchange
Equivariance to random image transformations is an effective method to l...
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RandLANet: Efficient Semantic Segmentation of LargeScale Point Clouds
We study the problem of efficient semantic segmentation for largescale ...
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Deep Hashing using Entropy Regularised Product Quantisation Network
In large scale systems, approximate nearest neighbour search is a crucia...
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Domain Partitioning Network
Standard adversarial training involves two agents, namely a generator an...
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AReS and MaRS  Adversarial and MMDMinimizing Regression for SDEs
Stochastic differential equations are an important modeling class in man...
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Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks
Recent deep monocular depth estimation approaches based on supervised re...
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Humanlike machine thinking: Language guided imagination
Human thinking requires the brain to understand the meaning of language ...
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BEHRT: Transformer for Electronic Health Records
Today, despite decades of developments in medicine and the growing inter...
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Cross Pixel Optical Flow Similarity for SelfSupervised Learning
We propose a novel method for learning convolutional neural image repres...
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