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08/16/2023
Atom-by-atom protein generation and beyond with language models
Protein language models learn powerful representations directly from seq...
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06/20/2023
Fast quantum algorithm for differential equations
Partial differential equations (PDEs) are ubiquitous in science and engi...
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05/09/2023
Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files
Language models are powerful tools for molecular design. Currently, the ...
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03/24/2023
Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting
Generating low-level robot task plans from high-level natural language i...
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02/22/2023
MVTrans: Multi-View Perception of Transparent Objects
Transparent object perception is a crucial skill for applications such a...
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02/07/2023
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library
String-based molecular representations play a crucial role in cheminform...
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12/19/2022
An Adaptive Robotics Framework for Chemistry Lab Automation
In the process of materials discovery, chemists currently need to perfor...
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12/03/2022
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
Deep learning models that leverage large datasets are often the state of...
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12/01/2022
One-shot recognition of any material anywhere using contrastive learning with physics-based rendering
We present MatSim: a synthetic dataset, a benchmark, and a method for co...
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11/27/2022
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions
In this paper, we introduce four main novelties: First, we present a new...
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11/23/2022
Group SELFIES: A Robust Fragment-Based Molecular String Representation
We introduce Group SELFIES, a molecular string representation that lever...
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10/19/2022
Machine Learning for a Sustainable Energy Future
Transitioning from fossil fuels to renewable energy sources is a critica...
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09/26/2022
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
The efficient exploration of chemical space to design molecules with int...
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07/06/2022
Quantum compression with classically simulatable circuits
As we continue to find applications where the currently available noisy ...
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04/04/2022
On scientific understanding with artificial intelligence
Imagine an oracle that correctly predicts the outcome of every particle ...
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03/31/2022
SELFIES and the future of molecular string representations
Artificial intelligence (AI) and machine learning (ML) are expanding in ...
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03/29/2022
Bayesian optimization with known experimental and design constraints for chemistry applications
Optimization strategies driven by machine learning, such as Bayesian opt...
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02/01/2022
Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning
Machine learning has the potential to automate molecular design and dras...
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12/06/2021
Keeping it Simple: Language Models can learn Complex Molecular Distributions
Deep generative models of molecules have grown immensely in popularity, ...
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10/20/2021
Learning quantum dynamics with latent neural ODEs
The core objective of machine-assisted scientific discovery is to learn ...
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09/30/2021
Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
The basis of many object manipulation algorithms is RGB-D input. Yet, co...
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09/27/2021
Design of quantum optical experiments with logic artificial intelligence
Logic artificial intelligence (AI) is a subfield of AI where variables c...
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09/15/2021
Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset
We present TransProteus, a dataset, and methods for predicting the 3D st...
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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...
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06/07/2021
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
Inverse molecular design, i.e., designing molecules with specific target...
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05/04/2021
Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction
This work explores the use of computer vision for image segmentation and...
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03/05/2021
Golem: An algorithm for robust experiment and process optimization
Numerous challenges in science and engineering can be framed as optimiza...
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03/05/2021
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation
Bayesian optimization has emerged as a powerful strategy to accelerate s...
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02/23/2021
Assigning Confidence to Molecular Property Prediction
Introduction: Computational modeling has rapidly advanced over the last ...
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01/21/2021
Noisy intermediate-scale quantum (NISQ) algorithms
A universal fault-tolerant quantum computer that can solve efficiently p...
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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...
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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...
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11/30/2020
Natural Evolutionary Strategies for Variational Quantum Computation
Natural evolutionary strategies (NES) are a family of gradient-free blac...
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11/03/2020
Bayesian Variational Optimization for Combinatorial Spaces
This paper focuses on Bayesian Optimization in combinatorial spaces. In ...
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10/27/2020
Scientific intuition inspired by machine learning generated hypotheses
Machine learning with application to questions in the physical sciences ...
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10/08/2020
Olympus: a benchmarking framework for noisy optimization and experiment planning
Research challenges encountered across science, engineering, and economi...
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06/02/2020
Experimental demonstration of a quantum generative adversarial network for continuous distributions
The potential advantage of machine learning in quantum computers is a to...
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03/26/2020
Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry
Designing functional molecules and advanced materials requires complex i...
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02/24/2020
Neural Message Passing on High Order Paths
Graph neural network have achieved impressive results in predicting mole...
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02/14/2020
Graph Deconvolutional Generation
Graph generation is an extremely important task, as graphs are found thr...
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10/23/2019
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
Predicting the relationship between a molecule's structure and its odor ...
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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...
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07/14/2019
An Artificial Spiking Quantum Neuron
Artificial spiking neural networks have found applications in areas wher...
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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...
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11/29/2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Deep generative models such as generative adversarial networks, variatio...
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01/04/2018
PHOENICS: A universal deep Bayesian optimizer
In this work we introduce PHOENICS, a probabilistic global optimization ...
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11/30/2017
Quantum Neuron: an elementary building block for machine learning on quantum computers
Even the most sophisticated artificial neural networks are built by aggr...
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09/12/2017
qTorch: The Quantum Tensor Contraction Handler
Classical simulation of quantum computation is necessary for studying th...
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07/20/2017
Machine Learning for Quantum Dynamics: Deep Learning of Excitation Energy Transfer Properties
Understanding the relationship between the structure of light-harvesting...
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06/06/2017
