Publications associées à Data Mining the C-C Cross-Coupling Genome

Publications associées (55)

On the added value of sequential deep learning for the upscaling of evapotranspiration

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

2025

Lewis acid catalyzed [4+2] annulation of bicyclobutanes with dienol ethers for the synthesis of bicyclo[4.1.1]octanes

Jérôme Waser, Stefano Nicolai

Bicyclic carbocycles containing a high fraction of Csp3 have become highly attractive synthetic targets because of the multiple applications they have found in medicinal chemistry. The formal cycloaddition of bicyclobutanes (BCBs) with two- or three-atom p ...

Royal Soc Chemistry2024

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

Strong coupling between a microwave photon and a singlet-triplet qubit

Pasquale Scarlino

Combining superconducting resonators and quantum dots has triggered tremendous progress in quantum information, however, attempts at coupling a resonator to even charge parity spin qubits have resulted only in weak spin-photon coupling. Here, we integrate ...

Nature Portfolio2024

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Zaffar Ahmed Shaikh

This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

PeerJ2025

Arylative Ring Expansion of 3-Vinylazetidin-3-Ols and 3-Vinyloxetan-3-Ols to Dihydrofurans by Dual Palladium and Acid Catalysis

Qian Wang, Jieping Zhu, Takuji Fujii

In contrast to the well-studied 1-vinylcyclobu- tanols, the reactivity of 3-vinylazetidin-3-ols 1 and 3- vinyloxetan-3-ols 2 under transition metal catalysis remains largely unexplored. We report herein their unique reactivity under dual palladium and acid ...

Wiley-VCH Verlag GmbH2024

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

Palladium-based supramolecular assemblies: from complex structures to water-soluble anion-receptors

Sylvain Alexandre Marie Sudan

The combination of palladium salts and bipyridyl ligands can lead to the formation of a large variety of coordination complexes, with different shapes and sizes, displaying a very versatile host-guest chemistry. Increasing their structural complexity remai ...

EPFL2024

Novel Alkynylation Methods through the Combination of Hypervalent Iodine Reagents and Alkynyl-trifluoroborate Salts

Julien Aymeric Borrel

The alkyne motif is a versatile functional group often encountered in organic chemistry. It can be involved in various transformations such as the alkyne-azide cycloaddition and has found widespread application in medicinal chemistry, chemical biology and ...

EPFL2024

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

Neural Garment Modeling

Ren Li

The digitization of 3D deformable objects remains a significant challenge in computer graphics and vision, particularly in the accurate modeling of garments. Garments exhibit complex shape variability, non-rigid deformations, and frequent self-occlusion, m ...

EPFL2025

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Jérôme Chenal, Baraka Jean-Claude Munyaka

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

AIP Publishing2025

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Pascal Fua

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Springer Science and Business Media Deutschland GmbH2025

Development of Hetero-Vinylbenziodoxolone Reagents for Applications in Synthetic Methodology and Biomolecule Functionalization

Nina Declas

Among the numerous existing chemical motifs, alkenes, alkynes, enol ethers and enamides, with an unsaturated carbon-carbon bond, are versatile functional groups that are found in many natural products and bioactive compounds. They are widely used as valuab ...

EPFL2023

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Zimin Xia

Given a ground-level query image and a geo-referenced aerial image that covers the query’s local surroundings, fine-grained cross-view localization aims to estimate the location of the ground camera inside the aerial image. Recent works have focused on dev ...

Springer Science and Business Media Deutschland GmbH2025

Photochemical [2+2] Cycloaddition of Alkynyl Boronates

Oleksandr Liashuk, Jérôme Waser

A photochemical [2+2] cycloaddition of alkynyl boronates and maleimides is reported. The developed protocol provided 35–70 % yield of maleimide-derived cyclobutenyl boronates and demonstrated wide compatibility with various functional groups. The synthetic ...

2023

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

Philippe Schwaller, Jeff Guo

Synthesizability in generative molecular design remains a pressing challenge. Existing methods to assess synthesizability include heuristics-based metrics or retrosynthesis models which predict a synthetic pathway. By contrast, an explicit approach anchors ...

ROYAL SOC CHEMISTRY2025

TiCl3-Mediated Reductive Cyclization of Tetrasubstituted Alkenes and Enol Esters Bearing a 2-Nitrophenyl Substituent

Dina Boyarskaya

Indole is one of the most important heterocycles widely present in bioactive natural products, pharmaceuticals, agrochemicals and materials. Being easily accessible, the 2-nitrostyrenes are attractive starting materials for the indole synthesis and the Cad ...

EPFL2023

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