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Max B. Paulus
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2020 – today
- 2023
- [b1]Max B. Paulus:
Learning with and for discrete optimization. ETH Zurich, Zürich, Switzerland, 2023 - [j1]Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun:
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1353-1371 (2023) - [c8]Rafael Sterzinger, Jan Poland, Max B. Paulus, Didier Chételat:
Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems. ISGT EUROPE 2023: 1-5 - [c7]Sirui Li, Wenbin Ouyang, Max B. Paulus, Cathy Wu:
Learning to Configure Separators in Branch-and-Cut. NeurIPS 2023 - [c6]Max B. Paulus, Andreas Krause:
Learning To Dive In Branch And Bound. NeurIPS 2023 - [i9]Max B. Paulus, Andreas Krause:
Learning To Dive In Branch And Bound. CoRR abs/2301.09943 (2023) - [i8]Sirui Li, Wenbin Ouyang, Max B. Paulus, Cathy Wu:
Learning to Configure Separators in Branch-and-Cut. CoRR abs/2311.05650 (2023) - 2022
- [c5]Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison:
Augment with Care: Contrastive Learning for Combinatorial Problems. ICML 2022: 5627-5642 - [c4]Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison:
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. ICML 2022: 17584-17600 - [c3]Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. NeurIPS 2022 - [i7]Romeo Valentin, Claudio Ferrari, Jérémy Scheurer, Andisheh Amrollahi, Chris Wendler, Max B. Paulus:
Instance-wise algorithm configuration with graph neural networks. CoRR abs/2202.04910 (2022) - [i6]Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison:
Augment with Care: Contrastive Learning for the Boolean Satisfiability Problem. CoRR abs/2202.08396 (2022) - [i5]Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison:
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning. CoRR abs/2206.13414 (2022) - [i4]Ðorðe Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. CoRR abs/2209.12590 (2022) - 2021
- [c2]Max B. Paulus, Chris J. Maddison, Andreas Krause:
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. ICLR 2021 - [i3]Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun:
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning. CoRR abs/2110.01515 (2021) - 2020
- [c1]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. NeurIPS 2020 - [i2]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. CoRR abs/2006.08063 (2020) - [i1]Max B. Paulus, Chris J. Maddison, Andreas Krause:
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. CoRR abs/2010.04838 (2020)
Coauthor Index
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