
Scalable QuasiBayesian Inference for Instrumental Variable Regression
Recent years have witnessed an upsurge of interest in employing flexible...
read it

A Novel Multiscale Dilated 3D CNN for Epileptic Seizure Prediction
Accurate prediction of epileptic seizures allows patients to take preven...
read it

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Standard dynamics models for continuous control make use of feedforward ...
read it

MirrorNeRF: Oneshot Neural Portrait RadianceField from Multimirror Catadioptric Imaging
Photorealistic neural reconstruction and rendering of the human portrai...
read it

Benchmarks for Deep OffPolicy Evaluation
Offpolicy evaluation (OPE) holds the promise of being able to leverage ...
read it

Regularized Behavior Value Estimation
Offline reinforcement learning restricts the learning process to rely on...
read it

Fork or Fail: CycleConsistent Training with ManytoOne Mappings
Cycleconsistent training is widely used for jointly learning a forward ...
read it

Offline Learning from Demonstrations and Unlabeled Experience
Behavior cloning (BC) is often practical for robot learning because it a...
read it

Further Analysis of Outlier Detection with Deep Generative Models
The recent, counterintuitive discovery that deep generative models (DGM...
read it

POP909: A Popsong Dataset for Music Arrangement Generation
Music arrangement generation is a subtask of automatic music generation,...
read it

Learning Interpretable Representation for Controllable Polyphonic Music Generation
While deep generative models have become the leading methods for algorit...
read it

PIANOTREE VAE: Structured Representation Learning for Polyphonic Music
The dominant approach for music representation learning involves the dee...
read it

Hyperparameter Selection for Offline Reinforcement Learning
Offline reinforcement learning (RL purely from logged data) is an import...
read it

Critic Regularized Regression
Offline reinforcement learning (RL), also known as batch RL, offers the ...
read it

RL Unplugged: Benchmarks for Offline Reinforcement Learning
Offline methods for reinforcement learning have the potential to help br...
read it

Acme: A Research Framework for Distributed Reinforcement Learning
Deep reinforcement learning has led to many recentand groundbreakingad...
read it

A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Score matching provides an effective approach to learning flexible unnor...
read it

Incentive Analysis of BitcoinNG, Revisited
BitcoinNG is among the first blockchain protocols to approach the near...
read it

The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
In narrow asymptotic settings Gaussian VAE models of continuous data hav...
read it

TaskRelevant Adversarial Imitation Learning
We show that a critical problem in adversarial imitation from highdimen...
read it

A Framework for DataDriven Robotics
We present a framework for datadriven robotics that makes use of a larg...
read it

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonst...
read it

Towards a MultiChain Future of ProofofSpace
ProofofSpace provides an intriguing alternative for consensus protocol...
read it

Deep Music Analogy Via Latent Representation Disentanglement
Analogy is a key solution to automated music generation, featured by its...
read it

Function Space Particle Optimization for Bayesian Neural Networks
While Bayesian neural networks (BNNs) have drawn increasing attention, t...
read it

A Framework for Automated Popsong Melody Generation with Piano Accompaniment Arrangement
We contribute a popsong automation framework for lead melody generation...
read it

Bayesian Optimization in AlphaGo
During the development of AlphaGo, its many hyperparameters were tuned ...
read it

OneShot HighFidelity Imitation: Training LargeScale Deep Nets with RL
Humans are experts at highfidelity imitation  closely mimicking a dem...
read it

Playing hard exploration games by watching YouTube
Deep reinforcement learning methods traditionally struggle with tasks wh...
read it

Reinforcement and Imitation Learning for Diverse Visuomotor Skills
We propose a modelfree deep reinforcement learning method that leverage...
read it

The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
This paper introduces the Intentional Unintentional (IU) agent. This age...
read it

Emergence of Locomotion Behaviours in Rich Environments
The reinforcement learning paradigm allows, in principle, for complex be...
read it

Parallel Multiscale Autoregressive Density Estimation
PixelCNN achieves stateoftheart results in density estimation for nat...
read it

Bayesian Optimisation for Machine Translation
This paper presents novel Bayesian optimisation algorithms for minimum e...
read it

Deep Fried Convnets
The fully connected layers of a deep convolutional neural network typica...
read it

Heteroscedastic Treed Bayesian Optimisation
Optimising blackbox functions is important in many disciplines, such as...
read it

Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process HyperParameters
Bayesian optimisation has gained great popularity as a tool for optimisi...
read it

Bayesian MultiScale Optimistic Optimization
Bayesian optimization is a powerful global optimization technique for ex...
read it

Bayesian Optimization in a Billion Dimensions via Random Embeddings
Bayesian optimization techniques have been successfully applied to robot...
read it

SelfAvoiding Random Dynamics on Integer Complex Systems
This paper introduces a new specialized algorithm for equilibrium Monte ...
read it

Bayesian Optimization for Adaptive MCMC
This paper proposes a new randomized strategy for adaptive MCMC using Ba...
read it
Ziyu Wang
verfied profile
Research Scientist at Google