Fetching the paper…
Reading the bibliography…
Spectroscopic techniques are essential tools for determining the structure of molecules.
Solvent effects in nuclear magnetic resonance spectra
AD Buckingham, T Schaefer, and WG Schneider · 1960
Earlier work this paper cites.
The Bayesian approach to global optimization
Jonas B Mockus · 1984
Earlier work this paper cites.
Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules
David Weininger · 1988
Earlier work this paper cites.
Development and testing of a general amber force field
Junmei Wang, Romain M Wolf, James W Caldwell, Peter A Kollman, and David A Case · 2004
Earlier work this paper cites.
Practical guide to interpretive near-infrared spectroscopy
Jerry Workman Jr and Lois Weyer · 2007
Earlier work this paper cites.
Nist 35. nist/epa gas-phase infrared database-jcamp format
Stephen E Stein · 2008
Earlier work this paper cites.
Extraction of chemical structures and reactions from the literature
Daniel Mark Lowe · 2012
Earlier work this paper cites.
Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2015
Earlier work this paper cites.
Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics
Arpana Vaniya and Oliver Fiehn · 2015
Earlier work this paper cites.
Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Fragmentation trees reloaded
Sebastian Böcker and Kai Dührkop · 2016
Earlier work this paper cites.
Sharing and community curation of mass spectrometry data with global natural products social molecular networking
Mingxun Wang, Jeremy J Carver, Vanessa V Phelan, Laura M Sanchez, Neha Garg, Yao Peng, Don Duy Nguyen, Jeramie Watrous, Clifford A Kapono, Tal Luzzatto-Knaan, et al · 2016
Earlier work this paper cites.
Calculating An IR Spectra From A Lammps Simulation, 2016
Efrem Braun · 2016
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Earlier work this paper cites.
Prediction of organic reaction outcomes using machine learning
Connor W Coley, Regina Barzilay, Tommi S Jaakkola, William H Green, and Klavs F Jensen · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
OpenNMT: Open-Source Toolkit for Neural Machine Translation, 2017
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander M. Rush · 2017
Earlier work this paper cites.
Planning chemical syntheses with deep neural networks and symbolic ai
Marwin HS Segler, Mike Preuss, and Mark P Waller · 2018
Earlier work this paper cites.
Machine learning in computer-aided synthesis planning
Connor W Coley, William H Green, and Klavs F Jensen · 2018
Earlier work this paper cites.
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli, Jennifer N Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D Hirzel, Ryan P Adams, and Alán Aspuru-Guzik · 2018
Earlier work this paper cites.
Junction tree variational autoencoder for molecular graph generation
Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2018
Earlier work this paper cites.
Deepsmiles: an adaptation of smiles for use in machine-learning of chemical structures
Noel O’Boyle and Andrew Dalke · 2018
Earlier work this paper cites.
Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction
Philippe Schwaller, Teodoro Laino, Théophile Gaudin, Peter Bolgar, Christopher A Hunter, Costas Bekas, and Alpha A Lee · 2019
Cited alongside, same era.
Deep imitation learning for molecular inverse problems
Eric Jonas · 2019
Cited alongside, same era.
Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy
Philippe Schwaller, Riccardo Petraglia, Valerio Zullo, Vishnu H Nair, Rico Andreas Haeuselmann, Riccardo Pisoni, Costas Bekas, Anna Iuliano, and Teodoro Laino · 2020
Cited alongside, same era.
Aizynthfinder: a fast, robust and flexible open-source software for retrosynthetic planning
Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist, and Esben Bjerrum · 2020
Cited alongside, same era.
Spectral deep learning for prediction and prospective validation of functional groups
Jonathan A Fine, Anand A Rajasekar, Krupal P Jethava, and Gaurav Chopra · 2020
Cited alongside, same era.
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
Later among the works it cites.
Coyo-700m: Image-text pair dataset
Minwoo Byeon, Beomhee Park, Haecheon Kim, Sungjun Lee, Woonhyuk Baek, and Saehoon Kim · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Deep reinforcement learning for molecular inverse problem of nuclear magnetic resonance spectra to molecular structure
Bhuvanesh Sridharan, Sarvesh Mehta, Yashaswi Pathak, and U Deva Priyakumar · 2022
Later among the works it cites.
Msnovelist: de novo structure generation from mass spectra
Michael A Stravs, Kai Dührkop, Sebastian Böcker, and Nicola Zamboni · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
matchms-processing and similarity evaluation of mass spectrometry data
Florian Huber, Stefan Verhoeven, Christiaan Meijer, Hanno Spreeuw, Efraín Manuel Villanueva Castilla, Cunliang Geng, Justin JJ van der Hooft, Simon Rogers, Adam Belloum, Faruk Diblen, et al · 2020
Cited alongside, same era.
Smarts. plus–a toolbox for chemical pattern design
Christiane Ehrt, Bennet Krause, Robert Schmidt, Emanuel SR Ehmki, and Matthias Rarey · 2020
Cited alongside, same era.
Self-referencing embedded strings (selfies): A 100% robust molecular string representation
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, and Alan Aspuru-Guzik · 2020
Cited alongside, same era.
Paccmannrl: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning
Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, Greta Markert, and María Rodríguez Martínez · 2021
Cited alongside, same era.
A framework for automated structure elucidation from routine nmr spectra
Zhaorui Huang, Michael S Chen, Cristian P Woroch, Thomas E Markland, and Matthew W Kanan · 2021
Cited alongside, same era.
Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding, and Radu Soricut · 2021
Cited alongside, same era.
Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
Cited alongside, same era.
Nist mass spectrum
NIST · 2022
Later among the works it cites.
Lammps-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
Aidan P Thompson, H Metin Aktulga, Richard Berger, Dan S Bolintineanu, W Michael Brown, Paul S Crozier, Pieter J In’t Veld, Axel Kohlmeyer, Stan G Moore, Trung Dac Nguyen, et al · 2022
Later among the works it cites.
Accelerated chemical reaction optimization using multi-task learning
Connor J Taylor, Kobi C Felton, Daniel Wigh, Mohammed I Jeraal, Rachel Grainger, Gianni Chessari, Christopher N Johnson, and Alexei A Lapkin · 2023
Later among the works it cites.
Bayesian optimization for chemical reactions
Jeff Guo, Bojana Ranković, and Philippe Schwaller · 2023
Later among the works it cites.
Accelerating material design with the generative toolkit for scientific discovery
Matteo Manica, Jannis Born, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Dean Clarke, Yves Gaetan Nana Teukam, Giorgio Giannone, Samuel C Hoffman, Matthew Buchan, et al · 2023
Later among the works it cites.
Infrared spectral analysis for prediction of functional groups based on feature-aggregated deep learning
Tianyi Wang, Ying Tan, Yu Zong Chen, and Chunyan Tan · 2023
Later among the works it cites.
Automatic materials characterization from infrared spectra using convolutional neural networks
Guwon Jung, Son Gyo Jung, and Jacqueline M Cole · 2023
Later among the works it cites.
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules
Samuel Goldman, John Bradshaw, Jiayi Xin, and Connor W. Coley · 2023
Later among the works it cites.
https://mestrelab.com/software/mnova/ (Accessed September 29, 2023)
MNova · 2023
Later among the works it cites.
Ambertools
David A Case, Hasan Metin Aktulga, Kellon Belfon, David S Cerutti, G Andrés Cisneros, Vinícius Wilian D Cruzeiro, Negin Forouzesh, Timothy J Giese, Andreas W Götz, Holger Gohlke, et al · 2023
Later among the works it cites.
Spectroscopy data for undergraduate teaching
Scott E Van Bramer and Loyd D Bastin · 2023
Later among the works it cites.
URL https://github.com/OpenNMT/OpenNMT-py
OpenNMT-py: Open-Source Neural Machine Translation, 2017 · 2023
Later among the works it cites.
4m: Massively multimodal masked modeling
David Mizrahi, Roman Bachmann, Oguzhan Kar, Teresa Yeo, Mingfei Gao, Afshin Dehghan, and Amir Zamir · 2024
Closest in time.
Twenty years of nmrshiftdb2: A case study of an open database for analytical chemistry
Stefan Kuhn, Heinz Kolshorn, Christoph Steinbeck, and Nils Schlörer · 2024
Closest in time.
Recent developments in machine learning for mass spectrometry
Armen G Beck, Matthew Muhoberac, Caitlin E Randolph, Connor H Beveridge, Prageeth R Wijewardhane, Hilkka I Kenttamaa, and Gaurav Chopra · 2024
Closest in time.
Generating Molecular Fragmentation Graphs with Autoregressive Neural Networks
Samuel Goldman, Janet Li, and Connor W. Coley · 2024
Closest in time.
Daylight chemical information systems
Daylight, online · 2024
Closest in time.
RDKit: Open-source cheminformatics
RDKit, online · 2024
Closest in time.