Back to directory 
2021-12
Learning to Combine Per-Example Solutions for Neural Program Synthesis
2021-08
Improving reproducibility in machine learning research : a report from the NeurIPS 2019 reproducibility program
Journal of Machine Learning Research
(2021-08-01)
hal.archives-ouvertes.frPDF[Also on arXiv preprint arXiv:2003.12206 (2020-03-27)]2021-07
Learning a Universal Template for Few-shot Dataset Generalization
2021-06
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches
2021-05
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles
Learning Flexible Classifiers with Shot-CONditional Episodic (SCONE) Training
Dependency Structure Discovery from Interventions
Uniform Priors for Data-Efficient Transfer
A Universal Representation Transformer Layer for Few-Shot Image Classification
2021-04
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark.
2021-03
Interpretable Multi-Modal Hate Speech Detection.
2021-02
Self-Supervised Equivariant Scene Synthesis from Video
2021-01
Impact of Aliasing on Generalization in Deep Convolutional Networks
ICCV 2021
(2021-01-01)
openaccess.thecvf.comPDF[LATEST on arXiv preprint arXiv:2108.03489 (2021-08-07)]2020-11
An Effective Anti-Aliasing Approach for Residual Networks.
Learned Equivariant Rendering without Transformation Supervision.
2020-07
Revisiting Fundamentals of Experience Replay
ICML 2020
(2020-07-12)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:2007.06700 (2020-07-13)]Small-GAN: Speeding up GAN Training using Core-Sets
2020-04
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Language GANs Falling Short
sistemas e métodos para realizar otimização bayesiana
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction.
2020-03
On-the-Fly Adaptation of Source Code Models using Meta-Learning
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
DIBS: Diversity inducing Information Bottleneck in Model Ensembles. (arXiv:2003.04514v1 [cs.LG])
arXiv Computer Science
(2020-03-11)
Diversity inducing Information Bottleneck in Model Ensembles.
Curriculum By Texture.
The Hanabi Challenge: A New Frontier for AI Research
2020-01
Acquiring and Predicting Multidimensional Diffusion (MUDI) Data: An Open Challenge
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Few-Shot Learning
Curriculum By Smoothing
Learning Graph Structure With A Finite-State Automaton Layer
On Catastrophic Interference in Atari 2600 Games
2019-09
Are Few-shot Learning Benchmarks Too Simple ?
2019-05
ICLR Reproducibility Challenge 2019
2019-03
A RAD approach to deep mixture models
A RAD approach to deep mixture models
2019-02
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-Time
Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification.
Hyperbolic Discounting and Learning over Multiple Horizons
2019-01
InfoBot: Transfer and Exploration via the Information Bottleneck
InfoBot: Structured Exploration in ReinforcementLearning Using Information Bottleneck
InfoBot: Transfer and Exploration via the Information Bottleneck
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
2018-11
Blindfold Baselines for Embodied QA.
2018-02
Disentangling the independently controllable factors of variation by interacting with the world
2018-01
HoME: a Household Multimodal Environment.
Publications collected and formatted using Paperoni
