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ORCIDMario Krenn
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2020 – today
- 2024
[j11]Tareq Jaouni
, Sören Arlt, Carlos Ruiz-Gonzalez, Ebrahim Karimi, Xuemei Gu, Mario Krenn:
Deep quantum graph dreaming: deciphering neural network insights into quantum experiments. Mach. Learn. Sci. Technol. 5(1): 15029 (2024)- [j10]Philipp Schmidt, Sören Arlt, Carlos Ruiz-Gonzalez, Xuemei Gu, Carla Rodríguez, Mario Krenn:
Virtual reality for understanding artificial-intelligence-driven scientific discovery with an application in quantum optics. Mach. Learn. Sci. Technol. 5(3): 35045 (2024) - [i22]Xuemei Gu, Mario Krenn:
Forecasting high-impact research topics via machine learning on evolving knowledge graphs. CoRR abs/2402.08640 (2024) - [i21]Philipp Schmidt, Sören Arlt, Carlos Ruiz-Gonzalez, Xuemei Gu, Carla Rodríguez, Mario Krenn:
Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics. CoRR abs/2403.00834 (2024) - [i20]Xuemei Gu, Mario Krenn:
Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models. CoRR abs/2405.17044 (2024) - [i19]Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, Mario Krenn:
Meta-Designing Quantum Experiments with Language Models. CoRR abs/2406.02470 (2024) - [i18]Felix Frohnert, Xuemei Gu, Mario Krenn, Evert P. L. van Nieuwenburg:
Discovering emergent connections in quantum physics research via dynamic word embeddings. CoRR abs/2411.06577 (2024) - 2023
- [j9]Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp:
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. Nat. Mac. Intell. 5(11): 1326-1335 (2023) - [j8]Carlos Ruiz-Gonzalez, Sören Arlt, Jan Petermann, Sharareh Sayyad, Tareq Jaouni, Ebrahim Karimi, Nora Tischler, Xuemei Gu, Mario Krenn:
Digital Discovery of 100 diverse Quantum Experiments with PyTheus. Quantum 7: 1204 (2023) - [i17]Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik:
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library. CoRR abs/2302.03620 (2023) - [i16]Tareq Jaouni, Sören Arlt, Carlos Ruiz-Gonzalez, Ebrahim Karimi, Xuemei Gu, Mario Krenn:
Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments. CoRR abs/2309.07056 (2023) - 2022
- [j7]Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik:
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning. Mach. Learn. Sci. Technol. 3(3): 35008 (2022) - [j6]Daniel Flam-Shepherd, Tony C. Wu, Xuemei Gu, Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Learning interpretable representations of entanglement in quantum optics experiments using deep generative models. Nat. Mach. Intell. 4(6): 544-554 (2022) - [j5]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. Patterns 3(10): 100588 (2022) - [j4]Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Design of quantum optical experiments with logic artificial intelligence. Quantum 6: 836 (2022) - [i15]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. CoRR abs/2204.00056 (2022) - [i14]Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabriel dos Passos Gomes, Florian Häse, Adrian Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru-Guzik:
On scientific understanding with artificial intelligence. CoRR abs/2204.01467 (2022) - [i13]Mario Krenn, Jonas Landgraf, Thomas Foesel, Florian Marquardt:
Artificial Intelligence and Machine Learning for Quantum Technologies. CoRR abs/2208.03836 (2022) - [i12]Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp:
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. CoRR abs/2210.00881 (2022) - 2021
- [j3]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. 2(2): 25027 (2021) - [j2]Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru-Guzik:
Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations. Mach. Learn. Sci. Technol. 2(3): 03 (2021) - [i11]Daniel Flam-Shepherd, Tony C. Wu, Xuemei Gu, Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models. CoRR abs/2109.02490 (2021) - [i10]Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Design of quantum optical experiments with logic artificial intelligence. CoRR abs/2109.13273 (2021) - 2020
- [j1]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. Mach. Learn. Sci. Technol. 1(4): 45024 (2020) - [c1]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR 2020 - [i9]Mario Krenn, Manuel Erhard, Anton Zeilinger:
Computer-inspired Quantum Experiments. CoRR abs/2002.09970 (2020) - [i8]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning generated hypotheses. CoRR abs/2010.14236 (2020) - [i7]Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru-Guzik:
Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations. CoRR abs/2012.09712 (2020) - [i6]Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik:
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning. CoRR abs/2012.11293 (2020)
2010 – 2019
- 2019
- [i5]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. CoRR abs/1905.13741 (2019) - [i4]Mario Krenn, Anton Zeilinger:
Predicting Research Trends with Semantic and Neural Networks with an application in Quantum Physics. CoRR abs/1906.06843 (2019) - [i3]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR abs/1909.11655 (2019) - [i2]Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter:
Quantum Optical Experiments Modeled by Long Short-Term Memory. CoRR abs/1910.13804 (2019) - 2017
- [i1]Alexey A. Melnikov, Hendrik Poulsen Nautrup, Mario Krenn, Vedran Dunjko, Markus Tiersch, Anton Zeilinger, Hans J. Briegel:
Active learning machine learns to create new quantum experiments. CoRR abs/1706.00868 (2017)
Coauthor Index
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