Data Mining the C-C Cross-Coupling Genome

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Coupling of space-separated resonators is interesting for quantum and communication technologies. In this work, we show that antiferromagnetic resonance in separated parallel-plane slabs of hematite (alpha-Fe2O3) couple cooperatively to terahertz electroma ...

Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

Efficient valorization of lignin, a sustainable source of functionalized aromatic products, would reduce dependence on fossil-derived feedstocks. Oxidative depolymerization is frequently applied to lignin to generate phenolic mono- mers. However, due to th ...

Self-supervised pretrained models exhibit competitive performance in automatic speech recognition (ASR) on finetuning, even with limited in-domain supervised data. However, popular pretrained models are not suitable for streaming ASR because they are train ...

Herein we report a mild synthesis of propargyl silanes from terminal alkynes. We exploit a bromonaphthyl-substituted silane as a silylmethyl electrophile surrogate, which participates in a Sonogashira reaction after an aryl-to-alkyl Pd-migration. Twenty-se ...

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 ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

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 ...

We experimentally demonstrate the coherent propagation of magnon polarons, the hybridized excitations formed by the coupling of spin waves and Rayleigh/Love surface acoustic waves, in a heterostructure consisting of ferroelectric BaTiO3 and ferromagnetic L ...

Automatic speech recognition (ASR) systems are well known to perform poorly on dysarthric speech. Previous works have addressed this by speaking rate modification to reduce the mismatch with typical speech. Unfortunately, these approaches rely on transcrib ...

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

The first two chapters develop ML-based models that generate conditional SDF estimates efficiently using conditioning information sets, resulting in minimal pricing errors and superior Sharpe ratios compared to traditional conditional asset pricing models. ...

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

The Birman-Williams theorem gives a connection between the collection of unstable periodic orbits (UPOs) contained within a chaotic attractor and the topology of that attractor, for three-dimensional systems. In certain cases, the fractal dimension of a ch ...

An enduring challenge in constructing mechanical-oscillator-based hybrid quantum systems is to ensure engineered coupling to an auxiliary degree of freedom and maintain good mechanical isolation from the environment, that is, low quantum decoherence, consi ...

Jointly estimating hand and object shape facilitates the grasping task in human-to-robot handovers. Relying on handcrafted prior knowledge about the geometric structure of the object fails when generalising to unseen objects, and depth sensors fail to dete ...

Alkynes are found in a multitude of natural or synthetic bioactive compounds. In addition to the capacity of these chemical motifs to impact the physicochemical properties of a molecule of interest, the well-established reactivity of alkynes makes them ide ...

Machine learning is increasingly integrated with decision making by powering automated systems and informing human decision makers in applications such as CV screening, portfolio allocation, loan risk assessment, and insurance approval. In this thesis, I e ...

Near-surface mercury and ozone depletion events occur in the lowest part of the atmosphere during Arctic spring. Mercury depletion is the first step in a process that transforms long-lived elemental mercury to more reactive forms within the Arctic that are ...

A robust anomaly detection mechanism should possess the capability to effectively remediate anomalies, restoring them to a healthy state, while preserving essential healthy information. Despite the efficacy of existing generative models in learning the und ...

Data Mining the C-C Cross-Coupling Genome

Chat with Graph Search

Cavity-Mediated Coupling of Terahertz Antiferromagnetic Resonators

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Direct conversion of lignin to functionalized diaryl ethers via oxidative cross-coupling

XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models

Synthesis of propargyl silanes from terminal alkynes via a migratory Sonogashira reaction

Diffusion Stochastic Optimization for Min-Max Problems

Validating functional redundancy with mixed generative adversarial networks

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

Long-distance coherent propagation of magnon polarons in a ferroelectric-ferromagnetic heterostructure

Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

Toward data-driven materials design: From atoms to pilot plants

Machine Learning Applications to Conditional Asset Pricing: Attention, CNNs, and Neural Tangent Kernels

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

The topology of a chaotic attractor in the Kuramoto-Sivashinsky equation

A squeezed mechanical oscillator with millisecond quantum decoherence

Stereo Hand-Object Reconstruction for Human-to-Robot Handover

Hypervalent Iodine: New Reagents and Functionalization of Peptides

Machine Learning in Decision-Making Systems: Fairness, Robustness, and Data Bias

Modelling the coupled mercury-halogen-ozone cycle in the central Arctic during spring

Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet