Understanding Joint Predictions in Machine Learning

Ian Osband is a Research scientist at OpenAI (ex DeepMind, Stanford) working on decision making under uncertainty.  

We spoke about: 

- Information theory and RL 

- Exploration, epistemic uncertainty and joint predictions 

- Epistemic Neural Networks and scaling to LLMs 

Featured References 

Reinforcement Learning, Bit by Bit 
Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen 

From Predictions to Decisions: The Importance of Joint Predictive Distributions 

Zheng Wen, Ian Osband, Chao Qin, Xiuyuan Lu, Morteza Ibrahimi, Vikranth Dwaracherla, Mohammad Asghari, Benjamin Van Roy  

Epistemic Neural Networks 

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy  

Approximate Thompson Sampling via Epistemic Neural Networks 

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy 

Additional References  

• Thesis defence, Ian Osband 
• Homepage, Ian Osband 
• Epistemic Neural Networks at Stanford RL Forum 
• Behaviour Suite for Reinforcement Learning, Osband et al 2019 
• Efficient Exploration for LLMs, Dwaracherla et al 2024