Jiaming Song

According to our database1, Jiaming Song authored at least 43 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
Robust and On-the-fly Dataset Denoising for Image Classification.
CoRR, 2020

Training Deep Energy-Based Models with f-Divergence Minimization.
CoRR, 2020

Gaussianization Flows.
CoRR, 2020

Permutation Invariant Graph Generation via Score-Based Generative Modeling.
CoRR, 2020

A Theory of Usable Information under Computational Constraints.
Proceedings of the 8th International Conference on Learning Representations, 2020

Understanding the Limitations of Variational Mutual Information Estimators.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Bridging the Gap Between $f$-GANs and Wasserstein GANs.
CoRR, 2019

Unsupervised Out-of-Distribution Detection with Batch Normalization.
CoRR, 2019

Cross Domain Imitation Learning.
CoRR, 2019

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multi-Agent Adversarial Inverse Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Calibrated Model-Based Deep Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bias Correction of Learned Generative Models via Likelihood-free Importance Weighting.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

A Scalable Sparse Matrix-Based Join for SPARQL Query Processing.
Proceedings of the Database Systems for Advanced Applications, 2019

A New Scheduling Model for Tire Production and Transportation Among Distributed Factories.
Proceedings of the 15th International Conference on Computational Intelligence and Security, 2019

Learning Controllable Fair Representations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

InfoVAE: Balancing Learning and Inference in Variational Autoencoders.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Malicious behaviour classification in web logs based on an improved Xgboost algorithm.
Int. J. Web Eng. Technol., 2018

gSMat: A Scalable Sparse Matrix-based Join for SPARQL Query Processing.
CoRR, 2018

The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models.
CoRR, 2018

An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients.
CoRR, 2018

Learning with Weak Supervision from Physics and Data-Driven Constraints.
AI Magazine, 2018

MapSQ: A Plugin-based MapReduce Framework for SPARQL Queries on GPU.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

A Lagrangian Perspective on Latent Variable Generative Models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Bias and Generalization in Deep Generative Models: An Empirical Study.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-Agent Generative Adversarial Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adversarial Constraint Learning for Structured Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
Proceedings of the 35th International Conference on Machine Learning, 2018

Char-Level Neural Network for Network Anomaly Behavior Detection.
Proceedings of the Human Centered Computing - 4th International Conference, 2018

2017
InfoVAE: Information Maximizing Variational Autoencoders.
CoRR, 2017

Towards Deeper Understanding of Variational Autoencoding Models.
CoRR, 2017

Learning Hierarchical Features from Generative Models.
CoRR, 2017

On the Limits of Learning Representations with Label-Based Supervision.
CoRR, 2017

Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs.
CoRR, 2017

A-NICE-MC: Adversarial Training for MCMC.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Hierarchical Features from Deep Generative Models.
Proceedings of the 34th International Conference on Machine Learning, 2017

Generative Adversarial Learning of Markov Chains.
Proceedings of the 5th International Conference on Learning Representations, 2017

SPARQL Query Parallel Processing: A Survey.
Proceedings of the 2017 IEEE International Congress on Big Data, 2017

2016
Max-Margin Nonparametric Latent Feature Models for Link Prediction.
CoRR, 2016

Factored Temporal Sigmoid Belief Networks for Sequence Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Online-offline consistency exploration based on the alternating direction method of multipliers.
Proceedings of the 11th International Conference on Computer Science & Education, 2016

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016


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