International Conference on Learning Representations (ICLR), 2019
Date
mai 6, 2019 — mai 9, 2019
Évènement
Date de soumission
sept. 27, 2018
Date de décision finale
déc. 19, 2018
Lieu
New Orleans, USA
Publications
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning.
International Conference on Learning Representations (ICLR),
2019.
Meta-Learning Framework with Applications to Zero-Shot Time Series Forecasting.
International Conference on Learning Representations (ICLR),
2019.
On Difficulties of Probability Distillation.
International Conference on Learning Representations (ICLR),
2019.
Probabilistic Planning with Sequential Monte Carlo Methods.
International Conference on Learning Representations (ICLR),
2019.
Quaternion Recurrent Neural Networks.
International Conference on Learning Representations (ICLR),
2019.
Systematic Generalization: What Is Required and Can It Be Learned?.
International Conference on Learning Representations (ICLR),
2019.
Adaptive Cross-Modal Few-shot Learning.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Adaptive Masked Weight Imprinting for Few-Shot Segmentation.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Adversarial Learning of General Transformations for Data Augmentation.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Adversarial Mixup Resynthesizers.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Planning with Latent SImulated Trajectories.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Towards Standardization of Data Licenses: The Montreal Data License.
Workshop at the International Conference on Learning Representations (ICLR),
2019.