Ruslan Salakhutdinov

Ruslan Salakhutdinov

Professor
Microsoft Faculty Fellow
Sloan Fellow
Carnegie Mellon University
rsalakhu[at]cs.cmu.edu
CV Google Scholar  

I am a UPMC professor of Computer Science in the Machine Learning Department, School of Computer Science at Carnegie Mellon University. I work in the field of statistical machine learning (See my CV.)

My research interests include Deep Learning, Probabilistic Graphical Models, and Large-scale Optimization.

Prospective students: Please read this to ensure that I read your email.

Recent Research Highlights:

• 4 part Deep Learning Tutorial at the Simons Institute, Berkeley
  Part 1:[Slides (pdf)], Part 2:[Slides (pdf)], Part 3:[Slides (pdf)], Part 4:[Slides (pdf)].
  
  
• Deep Learning Tutorial, MLSS, Tübingen, Germany
  Part 1:[Slides (pdf)], Part 2:[Slides (pdf)].
  
  
• I am co-teaching a Intermdiate Deep Learning class, Fall 2020.

Recent Papers:

• Effective Data Augmentation With Diffusion Models
  Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov
  ICLR 2023 Foundation Models Workshop [arXiv] [code]

• Generating Images with Multimodal Language Models
  Jing Yu Koh, Daniel Fried, Ruslan Salakhutdinov
  [arXiv] [code]

• Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
  Paul Pu Liang*, Zihao Deng*, Martin Ma*, James Zou, Louis-Philippe Morency, Ruslan Salakhutdinov
  [arXiv] [code]

• Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
  Paul Pu Liang, Chun Kai Ling, Yun Cheng, Alex Obolenskiy, Yudong Liu, Rohan Pandey, Alex Wilf, Louis-Philippe Morency, Ruslan Salakhutdinov
  [arXiv] [code]

• Quantifying & Modeling Feature Interactions: An Information Decomposition Framework
  Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard Chen, Zihao Deng, Nicholas Allen, Randy Auerbach, Faisal Mahmood, Ruslan Salakhutdinov, Louis-Philippe Morency
  [arXiv] [code]

• Imitating Task and Motion Planning with Visuomotor Transformers
  Murtaza Dalal*, Ajay Mandlekar, Caelan Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox
  [arXiv] [code]

• Graph Generative Model for Benchmarking Graph Neural Networks
  Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
  ICML 2023 [arXiv]

• A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
  Benjamin Eysenbach, Matthieu Geist, Sergey Levine, and Ruslan Salakhutdinov
  ICML 2023 [arXiv]

• Grounding Language Models to Images for Multimodal Inputs and Outputs
  Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried
  ICML 2023 [arXiv] [code]

• Multimodal Fusion Interactions: A Study of Human and Automatic Quantification
  Paul Pu Liang, Yun Cheng, Ruslan Salakhutdinov, Louis-Philippe Morency
  ICMI 2023 [arXiv] [code]

• Reasoning over Logically Interacted Conditions for Question Answering
  Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
  ICLR 2023 [arXiv]

• A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search
  Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov
  ICLR 2023 [arXiv]

• Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
  Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
  ICLR 2023 [arXiv]

• MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models
  Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, Ruslan Salakhutdinov
  ICLR 2023 [arXiv]