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05/30/2023
DualVAE: Controlling Colours of Generated and Real Images
Colour controlled image generation and manipulation are of interest to a...
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03/01/2023
R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents
Large language models show impressive results at predicting structured t...
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02/28/2023
Sampled Transformer for Point Sets
The sparse transformer can reduce the computational complexity of the se...
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01/27/2023
LegendreTron: Uprising Proper Multiclass Loss Learning
Loss functions serve as the foundation of supervised learning and are of...
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04/25/2022
Determinantal Point Process Likelihoods for Sequential Recommendation
Sequential recommendation is a popular task in academic research and clo...
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03/15/2022
SPA-VAE: Similar-Parts-Assignment for Unsupervised 3D Point Cloud Generation
This paper addresses the problem of unsupervised parts-aware point cloud...
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10/13/2021
EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation
This paper tackles the problem of parts-aware point cloud generation. Un...
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09/16/2021
Humanly Certifying Superhuman Classifiers
Estimating the performance of a machine learning system is a longstandin...
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03/06/2021
Learning to Continually Learn Rapidly from Few and Noisy Data
Neural networks suffer from catastrophic forgetting and are unable to se...
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02/19/2021
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
We propose a novel approach to interactive theorem-proving (ITP) using d...
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07/18/2020
MTL2L: A Context Aware Neural Optimiser
Learning to learn (L2L) trains a meta-learner to assist the learning of ...
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06/08/2020
All your loss are belong to Bayes
Loss functions are a cornerstone of machine learning and the starting po...
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09/10/2019
Computer Assisted Composition in Continuous Time
We address the problem of combining sequence models of symbolic music wi...
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05/25/2019
Sparse Gaussian Process Modulated Hawkes Process
The Hawkes process has been widely applied to modeling self-exciting eve...
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10/08/2018
Efficient Non-parametric Bayesian Hawkes Processes
In this paper, we develop a non-parametric Bayesian estimation of Hawkes...
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06/08/2018
Monge beats Bayes: Hardness Results for Adversarial Training
The last few years have seen extensive empirical study of the robustness...
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02/09/2018
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Prediction suffix trees (PST) provide an effective tool for sequence mod...
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12/01/2016
Computer Assisted Composition with Recurrent Neural Networks
Sequence modeling with neural networks has lead to powerful models of sy...
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06/08/2016