Benchmarks
Greatest papers with code
Discrete Autoencoders for Sequence Models
ICLR 2018
• tensorflow/tensor2tensor
• 
We propose to improve the representation in sequence models by augmenting current approaches with an autoencoder that is forced to compress the sequence through an intermediate discrete latent space.
HIERARCHICAL STRUCTURE LANGUAGE MODELLING MACHINE TRANSLATION
Benchmarking Deep Reinforcement Learning for Continuous Control
• openai/rllab
•
Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning.
Ranked #1 on
Continuous Control
on Cart-Pole Balancing
Poincaré Embeddings for Learning Hierarchical Representations
NeurIPS 2017
• facebookresearch/poincare-embeddings
• 
Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs.
Ranked #1 on
Lexical Entailment
on HyperLex
Skeleton-Aware Networks for Deep Motion Retargeting
• DeepMotionEditing/deep-motion-editing
•
In other words, our operators form the building blocks of a new deep motion processing framework that embeds the motion into a common latent space, shared by a collection of homeomorphic skeletons.
HIERARCHICAL STRUCTURE MOTION CAPTURE MOTION RETARGETING MOTION SYNTHESIS
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
• soroushmehr/sampleRNN_ICLR2017
• 
In this paper we propose a novel model for unconditional audio generation based on generating one audio sample at a time.
Meta-Learning for Semi-Supervised Few-Shot Classification
ICLR 2018
• yaoyao-liu/meta-transfer-learning
•
To address this paradigm, we propose novel extensions of Prototypical Networks (Snell et al., 2017) that are augmented with the ability to use unlabeled examples when producing prototypes.
EFANNA : An Extremely Fast Approximate Nearest Neighbor Search Algorithm Based on kNN Graph
In this paper, we propose EFANNA, an extremely fast approximate nearest neighbor search algorithm based on $k$NN Graph.
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
ICLR 2021
• budzianowski/multiwoz
•
We test HDNO on MultiWoz 2. 0 and MultiWoz 2. 1, the datasets on multi-domain dialogues, in comparison with word-level E2E model trained with RL, LaRL and HDSA, showing improvements on the performance evaluated by automatic evaluation metrics and human evaluation.
HIERARCHICAL REINFORCEMENT LEARNING HIERARCHICAL STRUCTURE TASK-ORIENTED DIALOGUE SYSTEMS
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks
• santi-pdp/pase
•
Learning good representations without supervision is still an open issue in machine learning, and is particularly challenging for speech signals, which are often characterized by long sequences with a complex hierarchical structure.
Ranked #2 on
Distant Speech Recognition
on DIRHA English WSJ
Whole-Body Human Pose Estimation in the Wild
This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet.
FACIAL LANDMARK DETECTION HAND POSE ESTIMATION HIERARCHICAL STRUCTURE