51³Ô¹ÏÍø

Seventeen papers by 51³Ô¹ÏÍø researchers from 4 departments will appear in the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

51³Ô¹ÏÍø researchers from three faculties and four departments had their work accepted to the 36^th Conference on Neural Information Processing Systems, or . These seventeen papers, from the Department of Computing, the Department of Electrical and Electronic Engineering, the Department of Mathematics, and the Business School, indicate the breadth and depth of focus into machine learning research at 51³Ô¹ÏÍø.

The accepted papers are:

• , , .
• John Birge, Xiaocheng Li, Chunlin Sun.
• Yanzhi Chen, Weihao Sun, , Adrian Weller. Scalable Infomin Learning
• , , Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, , Ruth Misener.
• Marton Havasi, , Finale Doshi-Velez. Addressing Leakage in Concept Bottleneck Models
• Clint Ho, Marek Petrik, Wolfram Wiesemann.
• Alexander Immer, , Gunnar Rätsch, Vincent Fortuin, .
• Yichong Leng*, *, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu.
• Shang Liu, Jiashuo Jiang, Xiaocheng Li.
• Zijing Ou, Tingyang Xu, Qinliang Su, , Peilin Zhao, Yatao Bian.
• Cristopher Salvi, Maud Lemercier, Andris Gerasimovics.
• Aras Selvi, Mohammadreza Belbasi, Martin Haugh, Wolfram Wiesemann.
• Harald Strömfelt, Luke Dickens, Artur Garcez, Alessandra Russo. Formalising Coherence and Consistency Applied to Transfer Learning in Neuro-Symbolic Autoencoders 
• Ryutaro Tanno, Melanie F. Pradier, Aditya Nori, .
• , Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener.
• Ben Tu, Axel Gandy, , Behrang Shafei.
• , David W. Romero, .