Max B. Paulus

According to our database, Max B. Paulus authored at least 13 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Learning with and for discrete optimization.

Max B. Paulus

PhD thesis, 2023

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning.

Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Learning To Dive In Branch And Bound.

Max B. Paulus, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Configure Separators in Branch-and-Cut.

Sirui Li, Wenbin Ouyang, Max B. Paulus, Cathy Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems.

Rafael Sterzinger, Jan Poland, Max B. Paulus, Didier Chételat

Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2023

2022

Augment with Care: Contrastive Learning for the Boolean Satisfiability Problem.

Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison

CoRR, 2022

Instance-wise algorithm configuration with graph neural networks.

Romeo Valentin, Claudio Ferrari, Jérémy Scheurer, Andisheh Amrollahi, Chris Wendler, Max B. Paulus

CoRR, 2022

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.

Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning.

Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison

Proceedings of the International Conference on Machine Learning, 2022

Augment with Care: Contrastive Learning for Combinatorial Problems.

Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison

Proceedings of the International Conference on Machine Learning, 2022

2021

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning.

Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun

CoRR, 2021

Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator.

Max B. Paulus, Chris J. Maddison, Andreas Krause

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Gradient Estimation with Stochastic Softmax Tricks.

Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020