Cover Image

Generative structural elucidation from mass spectra as an iterative optimization problem

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Manjrekar, Mrunali, Wang, Runzhong, Goldman, Samuel, Fromer, Jenna C., Coley, Connor W.
Format:	Preprint
Published:	2026
Subjects:	Quantitative Methods Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning
by: Wang, Runzhong, et al.
Published: (2025)

DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
by: Bohde, Montgomery, et al.
Published: (2025)

An algorithmic framework for synthetic cost-aware decision making in molecular design
by: Fromer, Jenna C., et al.
Published: (2023)

Recovering Sparse Neural Connectivity from Partial Measurements: A Covariance-Based Approach with Granger-Causality Refinement
by: Simeon, Quilee
Published: (2026)

Optimization of breeding program design through stochastic simulation with evolutionary algorithms
by: Hassanpour, Azadeh, et al.
Published: (2024)

FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time
by: Bohde, Montgomery, et al.
Published: (2026)

Selection of a Minimal Number of Significant Porcine SNPs by an Information Gain and Genetic Algorithm Hybrid Model
by: Rathasamuth, Wanthanee, et al.
Published: (2019)

LSTM networks provide efficient cyanobacterial blooms forecasting even with incomplete spatio-temporal data
by: Fournier, Claudia, et al.
Published: (2024)

Optimal compound downselection to promote diversity and parallel chemistry
by: Fromer, Jenna C., et al.
Published: (2025)

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery
by: Zhou, Andrew Y., et al.
Published: (2026)

On the Feasibility of Deep Learning Classification from Raw Signal Data in Radiology, Ultrasonography and Electrophysiology
by: Enyedi, Szilard
Published: (2024)

Effective Stimulus Propagation in Neural Circuits: Driver Node Selection
by: Batuev, Bulat, et al.
Published: (2025)

Deep-learning-based identification of individual motion characteristics from upper-limb trajectories towards disorder stage evaluation
by: Sziburis, Tim, et al.
Published: (2024)

Cognitive Neural Architecture Search Reveals Hierarchical Entailment
by: Kuhn, Lukas, et al.
Published: (2025)

Small Molecule Optimization with Large Language Models
by: Guevorguian, Philipp, et al.
Published: (2024)

Direct From Darwin: Deriving Advanced Optimizers From Evolutionary First Principles
by: Grimmer, Daniel
Published: (2026)

InputDSA: Demixing then Comparing Recurrent and Externally Driven Dynamics
by: Huang, Ann, et al.
Published: (2025)

Optimizing the Design of an Artificial Pancreas to Improve Diabetes Management
by: Khanna, Ashok, et al.
Published: (2024)

Coalitions of AI-based Methods Predict 15-Year Risks of Breast Cancer Metastasis Using Real-World Clinical Data with AUC up to 0.9
by: Jiang, Xia, et al.
Published: (2024)

Molecular Classification Using Hyperdimensional Graph Classification
by: Verges, Pere, et al.
Published: (2024)

Deep Learning: a Heuristic Three-stage Mechanism for Grid Searches to Optimize the Future Risk Prediction of Breast Cancer Metastasis Using EHR-based Clinical Data
by: Jiang, Xia, et al.
Published: (2024)

Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
by: Uehara, Masatoshi, et al.
Published: (2025)

Neural Population Decoding and Imbalanced Multi-Omic Datasets For Cancer Subtype Diagnosis
by: Kent, Charles Theodore, et al.
Published: (2024)

Deep Learning to Predict Late-Onset Breast Cancer Metastasis: the Single Hyperparameter Grid Search (SHGS) Strategy for Meta Tuning Concerning Deep Feed-forward Neural Network
by: Zhou, Yijun, et al.
Published: (2024)

Generating Molecular Fragmentation Graphs with Autoregressive Neural Networks
by: Goldman, Samuel, et al.
Published: (2023)

Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
by: Bal, Melis Ilayda, et al.
Published: (2024)

PRIMRose: Insights into the Per-Residue Energy Metrics of Proteins with Double InDel Mutations using Deep Learning
by: Brown, Stella, et al.
Published: (2025)

What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity
by: Bartolomé, Laura Alonso, et al.
Published: (2026)

NeuReg: Domain-invariant 3D Image Registration on Human and Mouse Brains
by: Razzaq, Taha, et al.
Published: (2024)

BIRDNet: Mining and Encoding Boolean Implication Knowledge Graphs as Interpretable Deep Neural Networks
by: Dash, Tirtharaj
Published: (2026)

Batched Bayesian optimization by maximizing the probability of including the optimum
by: Fromer, Jenna, et al.
Published: (2024)

Learning-guided iterated local search for the minmax multiple traveling salesman problem
by: He, Pengfei, et al.
Published: (2024)

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
by: Yu, Kevin, et al.
Published: (2024)

Deep memetic models for combinatorial optimization problems: application to the tool switching problem
by: Amaya, Jhon Edgar, et al.
Published: (2024)

RFI Detection with Spiking Neural Networks
by: Pritchard, Nicholas J., et al.
Published: (2023)

Advancing RFI-Detection in Radio Astronomy with Liquid State Machines
by: Pritchard, Nicholas J, et al.
Published: (2025)

Polarisation-Inclusive Spiking Neural Networks for Real-Time RFI Detection in Modern Radio Telescopes
by: Pritchard, Nicholas J., et al.
Published: (2025)

The Potential Impact of Neuromorphic Computing on Radio Telescope Observatories
by: Pritchard, Nicholas J., et al.
Published: (2026)

Spiking Neural Networks for Radio Frequency Interference Detection in Radio Astronomy
by: Pritchard, Nicholas J., et al.
Published: (2024)

Neuromorphic Astronomy: An End-to-End SNN Pipeline for RFI Detection Hardware
by: Pritchard, Nicholas J., et al.
Published: (2025)