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05/01/2023
Bird Distribution Modelling using Remote Sensing and Citizen Science data
Climate change is a major driver of biodiversity loss, changing the geog...
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11/15/2022
Teaching Algorithmic Reasoning via In-context Learning
Large language models (LLMs) have shown increasing in-context learning c...
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06/26/2022
Repository-Level Prompt Generation for Large Language Models of Code
With the success of large language models (LLMs) of code and their use a...
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04/02/2022
Matching Feature Sets for Few-Shot Image Classification
In image classification, it is common practice to train deep networks to...
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03/07/2022
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions
The execution behavior of a program often depends on external resources,...
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02/01/2022
Fortuitous Forgetting in Connectionist Networks
Forgetting is often seen as an unwanted characteristic in both human and...
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01/10/2022
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
Transfer-learning methods aim to improve performance in a data-scarce ta...
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08/07/2021
Impact of Aliasing on Generalization in Deep Convolutional Networks
We investigate the impact of aliasing on generalization in Deep Convolut...
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06/14/2021
Learning to Combine Per-Example Solutions for Neural Program Synthesis
The goal of program synthesis from examples is to find a computer progra...
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05/14/2021
Learning a Universal Template for Few-shot Dataset Generalization
Few-shot dataset generalization is a challenging variant of the well-stu...
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04/06/2021
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Meta and transfer learning are two successful families of approaches to ...
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03/02/2021
Interpretable Multi-Modal Hate Speech Detection
With growing role of social media in shaping public opinions and beliefs...
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02/01/2021
Self-Supervised Equivariant Scene Synthesis from Video
We propose a self-supervised framework to learn scene representations fr...
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11/11/2020
Learned Equivariant Rendering without Transformation Supervision
We propose a self-supervised framework to learn scene representations fr...
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10/23/2020
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Graph neural networks (GNNs) have emerged as a powerful tool for learnin...
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07/13/2020
Revisiting Fundamentals of Experience Replay
Experience replay is central to off-policy algorithms in deep reinforcem...
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07/09/2020
Learning Graph Structure With A Finite-State Automaton Layer
Graph-based neural network models are producing strong results in a numb...
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06/21/2020
A Universal Representation Transformer Layer for Few-Shot Image Classification
Few-shot classification aims to recognize unseen classes when presented ...
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03/27/2020
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)
One of the challenges in machine learning research is to ensure that pre...
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03/26/2020
On-the-Fly Adaptation of Source Code Models using Meta-Learning
The ability to adapt to unseen, local contexts is an important challenge...
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03/12/2020
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
We show that the sum of the implicit generator log-density log p_g of a ...
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03/10/2020
DIBS: Diversity inducing Information Bottleneck in Model Ensembles
Although deep learning models have achieved state-of-the-art performance...
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03/03/2020
Curriculum By Texture
Convolutional Neural Networks (CNNs) have shown impressive performance i...
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02/28/2020
On Catastrophic Interference in Atari 2600 Games
Model-free deep reinforcement learning algorithms are troubled with poor...
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11/28/2019
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction
Text-based games are a natural challenge domain for deep reinforcement l...
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10/29/2019
Small-GAN: Speeding Up GAN Training Using Core-sets
Recent work by Brock et al. (2018) suggests that Generative Adversarial ...
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10/02/2019
Learning Neural Causal Models from Unknown Interventions
Meta-learning over a set of distributions can be interpreted as learning...
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03/18/2019
A RAD approach to deep mixture models
Flow based models such as Real NVP are an extremely powerful approach to...
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03/07/2019
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Few-shot classification refers to learning a classifier for new classes ...
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02/22/2019
Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification
Traditional clustering algorithms such as K-means rely heavily on the na...
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02/19/2019
Hyperbolic Discounting and Learning over Multiple Horizons
Reinforcement learning (RL) typically defines a discount factor as part ...
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02/01/2019
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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01/30/2019
InfoBot: Transfer and Exploration via the Information Bottleneck
A central challenge in reinforcement learning is discovering effective p...
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11/12/2018
Blindfold Baselines for Embodied QA
We explore blindfold (question-only) baselines for Embodied Question Ans...
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11/06/2018
Language GANs Falling Short
Generating high-quality text with sufficient diversity is essential for ...
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04/02/2018
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
In many environments only a tiny subset of all states yield high reward....
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03/02/2018
Meta-Learning for Semi-Supervised Few-Shot Classification
In few-shot classification, we are interested in learning algorithms tha...
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02/26/2018
Disentangling the independently controllable factors of variation by interacting with the world
It has been postulated that a good representation is one that disentangl...
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11/29/2017
HoME: a Household Multimodal Environment
We introduce HoME: a Household Multimodal Environment for artificial age...
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07/03/2017
Multiscale sequence modeling with a learned dictionary
We propose a generalization of neural network sequence models. Instead o...
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07/02/2017
Modulating early visual processing by language
It is commonly assumed that language refers to high-level visual concept...
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11/23/2016
GuessWhat?! Visual object discovery through multi-modal dialogue
We introduce GuessWhat?!, a two-player guessing game as a testbed for re...
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07/18/2016
Deep learning trends for focal brain pathology segmentation in MRI
Segmentation of focal (localized) brain pathologies such as brain tumors...
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05/24/2016
Hierarchical Memory Networks
Memory networks are neural networks with an explicit memory component th...
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05/12/2016
Movie Description
Audio Description (AD) provides linguistic descriptions of movies and al...
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05/07/2016
Neural Autoregressive Distribution Estimation
We present Neural Autoregressive Distribution Estimation (NADE) models, ...
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03/27/2016
Recurrent Mixture Density Network for Spatiotemporal Visual Attention
In many computer vision tasks, the relevant information to solve the pro...
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03/18/2016
Document Neural Autoregressive Distribution Estimation
We present an approach based on feed-forward neural networks for learnin...
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12/31/2015
Autoencoding beyond pixels using a learned similarity metric
We present an autoencoder that leverages learned representations to bett...
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11/24/2015