Co-occurring keywords · papers mentioning both
Papers
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
NeurIPS 2020
Revisiting Spatial Invariance with Low-Rank Local Connectivity
ICML 2020
Towards a Deep Network Architecture for Structured Smoothness
ICLR 2020
Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation
EMNLP 2019
An Investigation of Model-Free Planning
ICML 2019
Auto-Encoding Scene Graphs for Image Captioning
CVPR 2019
Biases for Emergent Communication in Multi-agent Reinforcement Learning
NeurIPS 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
ICML 2019
Cognitive model priors for predicting human decisions
ICML 2019
Evaluating Lottery Tickets Under Distributional Shifts
EMNLP 2019
Feature-Wise Bias Amplification
ICLR 2019
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
NeurIPS 2019
HMEAE: Hierarchical Modular Event Argument Extraction
EMNLP 2019
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
NAACL 2019
Language Learning and Processing in People and Machines
NAACL 2019
Learning dynamic polynomial proofs
NeurIPS 2019
Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs
EMNLP 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
NeurIPS 2019
On the Inductive Bias of Neural Tangent Kernels
NeurIPS 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
NeurIPS 2019
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
ICLR 2019
Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages
NAACL 2019
Symbolic Inductive Bias for Visually Grounded Learning of Spoken Language
ACL 2019
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation
ACL 2018
Bias and Generalization in Deep Generative Models: An Empirical Study
NeurIPS 2018