Publications associées à Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

Publications associées (13)

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Anne-Clémence Corminboeuf, Friedrich Eisenbrand, Rubén Laplaza Solanas, Puck Elisabeth van Gerwen, Ksenia Briling, Jan Weinreich, Matthieu Nicolas Haeberle

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

IOP Publishing Ltd2025

A shortcut model for batch distillation columns using pertinent effective factors

Dominique Bonvin

A shortcut model is a low-order model that provides a simplified representation of a complex process, thereby enabling faster and more efficient analysis, design and optimization without the computational intensity of a full-scale model. For continuous dis ...

Elsevier2025

Diffusion Stochastic Optimization for Min-Max Problems

Ali H. Sayed, Haoyuan Cai

The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of O(ϵ-2) to achieve an ϵ-stationary solut ...

2025

Coherent magnon transport in a van der Waals antiferromagnet

Jean-Philippe Ansermet

Recently developed van der Waals magnets offer a promising platform for advancing spintronics. The weak interlayer antiferromagnetic exchange coupling in van der Waals antiferromagnets allows for unique spin dynamics and control over magnons. In this study ...

AIP Publishing2025

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Ramin Mohammadi, Nikolaos Stergiopoulos, Georgios Rovas, Lydia Aslanidou, Sokratis Anagnostopoulos

Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

2025

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Michael Lehning, Devis Tuia, Yael Frischholz

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

2025

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Su Yeon Chang

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

IOP Publishing Ltd2025

Edge-Cloud Collaborated Object Detection via Bandwidth Adaptive Difficult-Case Discriminator

Yung-Cheng Chiang

Object detection, a fundamental task in computer vision, is crucial for various intelligent edge computing applications. However, object detection algorithms are usually heavy in computation, hindering their deployments on resource-constrained edge devices ...

2025

Convex Computation of Value-at-risk Bounds for Stochastic Processes

Matteo Raphael Tacchi

This article formulates algorithms to upper-bound the maximum value-at-risk (VaR) of a state function along trajectories of stochastic processes. The VaR is upper bounded by two methods: minimax tail-bounds (Cantelli/Vysochanskij-Petunin) and Expected Shor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

GLoFool: Global Enhancements and Local Perturbations to Craft Adversarial Images

Andrea Cavallaro

Adversarial examples crafted in black-box scenarios are affected by unrealistic colors or spatial artifacts. To prevent these shortcomings, we propose a novel strategy that generates adversarial images with low detectability and high transferability. The p ...

Springer Science and Business Media Deutschland GmbH2025

Search for Heavy Neutral Resonances Decaying to Tau Lepton Pairs in Proton-proton Collisions at √s=13 Tev

Jan Steggemann, Konstantin Androsov, Anna Mascellani, Joanna Malgorzata Wanczyk

A search for heavy neutral gauge bosons (Z ') decaying into a pair of tau leptons is performed in proton-proton collisions at root s = 13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 f ...

AMER PHYSICAL SOC2025

Dimensionless Group-Driven Ensemble Neural Networks for Robust Design Optimisation in Engineering

Jürg Alexander Schiffmann, Soheyl Massoudi

This work aims to develop a scalable surrogate modelling framework for robust multidisciplinary design optimisation (RMDO) in complex engineering systems. Focusing on gas-bearing supported rotors, it addresses the need to maintain system performance under ...

Oxford University Press (OUP)2025

Enabling Deep Learning Models for Seizure Monitoring within Wearables Lifecycle

Alireza Amirshahi

Continuous monitoring of various physiological conditions enables early detection of potential health issues. The monitoring offers real-time insights into patient well-being and rapid medical interventions. As a case study, in epilepsy, a prevalent neurol ...

EPFL2025