Alán Aspuru-Guzik

Orcid: 0000-0002-8277-4434

According to our database1, Alán Aspuru-Guzik authored at least 105 papers between 2005 and 2024.

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Bibliography

2024
Towards the prediction of drug solubility in binary solvent mixtures at various temperatures using machine learning.
J. Cheminformatics, December, 2024

Accelerating discovery in organic redox flow batteries.
Nat. Comput. Sci., 2024

Closed-loop transfer enables artificial intelligence to yield chemical knowledge.
Nat., 2024

Range-separated density functional theory using multiresolution analysis and quantum computing.
J. Comput. Chem., 2024

How to do impactful research in artificial intelligence for chemistry and materials science.
CoRR, 2024

A theory of understanding for artificial intelligence: composability, catalysts, and learning.
CoRR, 2024

Efficient Evolutionary Search Over Chemical Space with Large Language Models.
CoRR, 2024

Application-Driven Innovation in Machine Learning.
CoRR, 2024

Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data.
CoRR, 2024

Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS.
CoRR, 2024

Chemically Motivated Simulation Problems are Efficiently Solvable by a Quantum Computer.
CoRR, 2024

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization.
CoRR, 2024

RePLan: Robotic Replanning with Perception and Language Models.
CoRR, 2024

Position: Application-Driven Innovation in Machine Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Large language models for chemistry robotics.
Auton. Robots, December, 2023

Augmenting Polymer Datasets by Iterative Rearrangement.
J. Chem. Inf. Model., July, 2023

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.
J. Chem. Inf. Model., June, 2023

Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks.
Nat. Comput. Sci., 2023

Sorting Out Quantum Monte Carlo.
CoRR, 2023

Towards equilibrium molecular conformation generation with GFlowNets.
CoRR, 2023

Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance.
CoRR, 2023

Atom-by-atom protein generation and beyond with language models.
CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR, 2023

Fast quantum algorithm for differential equations.
CoRR, 2023

Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files.
CoRR, 2023

Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting.
CoRR, 2023

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library.
CoRR, 2023

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023


MVTrans: Multi-View Perception of Transparent Objects.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

One-shot recognition of any material anywhere using contrastive learning with physics-based rendering.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Design of quantum optical experiments with logic artificial intelligence.
Quantum, September, 2022

SELFIES and the future of molecular string representations.
Patterns, 2022

Learning interpretable representations of entanglement in quantum optics experiments using deep generative models.
Nat. Mach. Intell., 2022

Reinforcement learning supercharges redox flow batteries.
Nat. Mach. Intell., 2022

Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning.
Mach. Learn. Sci. Technol., 2022

Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines.
J. Chem. Inf. Model., 2022

An Adaptive Robotics Framework for Chemistry Lab Automation.
CoRR, 2022

Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS.
CoRR, 2022

Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions.
CoRR, 2022

Group SELFIES: A Robust Fragment-Based Molecular String Representation.
CoRR, 2022

Machine Learning for a Sustainable Energy Future.
CoRR, 2022

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
CoRR, 2022

Quantum compression with classically simulatable circuits.
CoRR, 2022

On scientific understanding with artificial intelligence.
CoRR, 2022

Bayesian optimization with known experimental and design constraints for chemistry applications.
CoRR, 2022

Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning.
CoRR, 2022

AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor.
CoRR, 2022

2021
Olympus: a benchmarking framework for noisy optimization and experiment planning.
Mach. Learn. Sci. Technol., September, 2021

Inverse design of nanoporous crystalline reticular materials with deep generative models.
Nat. Mach. Intell., 2021

Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations.
Mach. Learn. Sci. Technol., 2021

The influence of sorbitol doping on aggregation and electronic properties of PEDOT: PSS: a theoretical study.
Mach. Learn. Sci. Technol., 2021

Scientific intuition inspired by machine learning-generated hypotheses.
Mach. Learn. Sci. Technol., 2021

Neural message passing on high order paths.
Mach. Learn. Sci. Technol., 2021

MPGVAE: improved generation of small organic molecules using message passing neural nets.
Mach. Learn. Sci. Technol., 2021

Natural evolutionary strategies for variational quantum computation.
Mach. Learn. Sci. Technol., 2021

funsies: A minimalist, distributed and dynamic workflow engine.
J. Open Source Softw., 2021

Keeping it Simple: Language Models can learn Complex Molecular Distributions.
CoRR, 2021

Learning quantum dynamics with latent neural ODEs.
CoRR, 2021

Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset.
CoRR, 2021

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design.
CoRR, 2021

Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction.
CoRR, 2021

Golem: An algorithm for robust experiment and process optimization.
CoRR, 2021

Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation.
CoRR, 2021

Assigning Confidence to Molecular Property Prediction.
CoRR, 2021

Noisy intermediate-scale quantum (NISQ) algorithms.
CoRR, 2021

Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization.
Quantum, 2020

A machine learning workflow for molecular analysis: application to melting points.
Mach. Learn. Sci. Technol., 2020

Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation.
Mach. Learn. Sci. Technol., 2020

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning.
CoRR, 2020

Bayesian Variational Optimization for Combinatorial Spaces.
CoRR, 2020

Experimental demonstration of a quantum generative adversarial network for continuous distributions.
CoRR, 2020

Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry.
CoRR, 2020

Graph Deconvolutional Generation.
CoRR, 2020

Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Quantum Coherences as a Thermodynamic Potential.
Open Syst. Inf. Dyn., 2019

Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules.
CoRR, 2019

Generator evaluator-selector net: a modular approach for panoptic segmentation.
CoRR, 2019

An Artificial Spiking Quantum Neuron.
CoRR, 2019

SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry.
CoRR, 2019

2018
ChemOS: Orchestrating autonomous experimentation.
Sci. Robotics, 2018

Quantum chemistry reveals thermodynamic principles of redox biochemistry.
PLoS Comput. Biol., 2018

Reinforced Adversarial Neural Computer for de Novo Molecular Design.
J. Chem. Inf. Model., 2018

Potential of quantum computing for drug discovery.
IBM J. Res. Dev., 2018

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.
CoRR, 2018

2017
Emulation of complex open quantum systems using superconducting qubits.
Quantum Inf. Process., 2017

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.
J. Chem. Inf. Model., 2017

Quantum Neuron: an elementary building block for machine learning on quantum computers.
CoRR, 2017

qTorch: The Quantum Tensor Contraction Handler.
CoRR, 2017

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models.
CoRR, 2017

Variational Quantum Factoring.
Proceedings of the Quantum Technology and Optimization Problems, 2017

Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
qHiPSTER: The Quantum High Performance Software Testing Environment.
CoRR, 2016

Automatic chemical design using a data-driven continuous representation of molecules.
CoRR, 2016

2015
Faster than Classical Quantum Algorithm for dense Formulas of Exact Satisfiability and Occupation Problems.
CoRR, 2015

Convolutional Networks on Graphs for Learning Molecular Fingerprints.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Bayesian Network Structure Learning Using Quantum Annealing.
CoRR, 2014

2013
Computational complexity of time-dependent density functional theory.
CoRR, 2013

2012
Computational Complexity in Electronic Structure
CoRR, 2012

2011
A study of heuristic guesses for adiabatic quantum computation.
Quantum Inf. Process., 2011

2010
Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units.
Comput. Sci. Eng., 2010

2005
Zori 1.0: A parallel quantum Monte Carlo electronic structure package.
J. Comput. Chem., 2005

A sparse algorithm for the evaluation of the local energy in quantum Monte Carlo.
J. Comput. Chem., 2005


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