Mario Krenn | DeepAI

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∙ 09/13/2023

Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments

Despite their promise to facilitate new scientific discoveries, the opaq...

0 Tareq Jaouni, et al. ∙

∙ 02/07/2023

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library

String-based molecular representations play a crucial role in cheminform...

0 Alston Lo, et al. ∙

∙ 08/07/2022

Artificial Intelligence and Machine Learning for Quantum Technologies

In recent years, the dramatic progress in machine learning has begun to ...

6 Mario Krenn, et al. ∙

∙ 04/04/2022

On scientific understanding with artificial intelligence

Imagine an oracle that correctly predicts the outcome of every particle ...

33 Mario Krenn, et al. ∙

∙ 03/31/2022

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in ...

0 Mario Krenn, et al. ∙

∙ 09/27/2021

Design of quantum optical experiments with logic artificial intelligence

Logic artificial intelligence (AI) is a subfield of AI where variables c...

0 Alba Cervera-Lierta, et al. ∙

∙ 09/06/2021

Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models

Quantum physics experiments produce interesting phenomena such as interf...

30 Daniel Flam-Shepherd, et al. ∙

∙ 12/17/2020

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning

Computer-aided design of molecules has the potential to disrupt the fiel...

0 Luca A. Thiede, et al. ∙

∙ 12/17/2020

Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations

Computer-based de-novo design of functional molecules is one of the most...

0 Cynthia Shen, et al. ∙

∙ 10/27/2020

Scientific intuition inspired by machine learning generated hypotheses

Machine learning with application to questions in the physical sciences ...

0 Pascal Friederich, et al. ∙

∙ 02/23/2020

Computer-inspired Quantum Experiments

The design of new devices and experiments in science and engineering has...

0 Mario Krenn, et al. ∙

∙ 10/30/2019

Quantum Optical Experiments Modeled by Long Short-Term Memory

We demonstrate how machine learning is able to model experiments in quan...

40 Thomas Adler, et al. ∙

∙ 09/25/2019

Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space

Challenges in natural sciences can often be phrased as optimization prob...

0 AkshatKumar Nigam, et al. ∙

∙ 06/17/2019

Predicting Research Trends with Semantic and Neural Networks with an application in Quantum Physics

The vast and growing number of publications in all disciplines of scienc...

0 Mario Krenn, et al. ∙

∙ 05/31/2019

SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry

Graphs are ideal representations of complex, relational information. The...

0 Mario Krenn, et al. ∙

∙ 06/02/2017

Active learning machine learns to create new quantum experiments

How useful can machine learning be in a quantum laboratory? Here we rais...

0 Alexey A. Melnikov, et al. ∙

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