Talks

• Estimating the Rate-Distortion Function with Statistical Learning and Optimal Transport Invited talk at Stanford information theory forum. Nov 3, 2023.
  ITA Workshop graduation day presentation. Feb 21, 2024. (best student presentation)
  [slides]

Conference Papers

• Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
  Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt
  Conference on Neural Information Processing Systems (NeurIPS), 2023
  [pdf] [code] [slides] [poster]

• Computationally-Efficient Neural Image Compression with Shallow Decoders
  Yibo Yang, Stephan Mandt
  International Conference on Computer Vision (ICCV), 2023
  [pdf] [code] [poster]

• Towards Empirical Sandwich Bounds on the Rate-Distortion Function
  Yibo Yang, Stephan Mandt
  International Conference on Learning Representations (ICLR), 2022
  [pdf] [code] [talk] [poster] [blog post]

• Hierarchical Autoregressive Modeling for Neural Video Compression
  Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
  International Conference on Learning Representations (ICLR), 2021
  [pdf]

• Improving Inference for Neural Image Compression
  Yibo Yang, Robert Bamler, and Stephan Mandt
  Conference on Neural Information Processing Systems (NeurIPS), 2020
  [pdf] [code] [talk] [poster]

• Variational Bayesian Quantization
  Yibo Yang*, Robert Bamler*, and Stephan Mandt
  International Conference on Machine Learning (ICML), 2020
  [pdf] [code] [slides]

• Lifted Hybrid Variational Inference
  Yuqiao Chen*, Yibo Yang*, Sriraam Natarajan, and Nicholas Ruozzi
  International Joint Conference on Artificial Intelligence (IJCAI), 2020
  [pdf]

• One-Shot Marginal MAP Inference in Markov Random Fields
  Hao Xiong*, Yuanzhen Guo*, Yibo Yang*, and Nicholas Ruozzi
  Uncertainty in Artificial Intelligence (UAI), 2019
  [pdf]

Journals

• An Introduction to Neural Data Compression
  Yibo Yang, Stephan Mandt, Lucas Theis
  Foundations and Trends in Computer Graphics and Vision, 15(2), 113-200, 2023
  [pdf] [cite] [video lecture]

• Insights from Generative Modeling for Neural Video Compression
  Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
  Transactions on Pattern Analysis and Machine Intelligence, 2023
  [pdf]

• Foundations of a Fast, Data-Driven, Machine-Learned Simulator
  Jessica N. Howard, Stephan Mandt, Daniel Whiteson, Yibo Yang (alphabetical order)
  Nature Scientific Reports
  [pdf] [talk]

Workshop Papers

• Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
  Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt
  ICML 2023 Workshop on Neural Compression (spotlight)
  [pdf]

• Autoencoding Implicit Neural Representations for Image Compression
  Tuan Pham, Yibo Yang, Stephan Mandt
  ICML 2023 Workshop on Neural Compression
  [pdf]

• Lower Bounding Rate-Distortion From Samples
  Yibo Yang, Stephan Mandt
  ICLR 2021 Workshop on Neural Compression: From Information Theory to Applications (spotlight)
  [pdf] [talk]

• Deep Generative Video Compression with Temporal Autoregressive Transform
  Ruihan Yang, Yibo Yang, Joseph Marino, Yang Yang, Stephan Mandt
  ICML 2020 Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models
  [pdf]

• Efficient Neural Network Pruning and Quantization by Hard Clustering
  Yibo Yang, Nicholas Ruozzi, Vibhav Gogate
  AAAI 2019 Workshop on Network Interpretability for Deep Learning
  [pdf]

* denotes equal contribution.