Publications related to A benchmark dataset for machine learning in ecotoxicology

Related publications (39)

Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Dirk Grundler, Andrea Mucchietto, Mingran Xu, Kyongmo An

Nonlinearity of dynamic systems plays a key role in neuromorphic computing, which is expected to reduce the ever-increasing power consumption of machine learning and artificial intelligence applications. For spin waves (magnons), nonlinearity combined with ...

Nature Research2024

Deep Architectural Form

Frederick Chando Kim

With recent innovations in artificial intelligence (AI), machines can now recognize architectural patterns and generate new forms in ways that far exceed human capacity. The integration of machines in the design process has ushered in a substantial shift i ...

EPFL2024

Learning Motion Reconstruction from Demonstration via Multi-Modal Soft Tactile Sensing

Josephine Anna Eleanor Hughes, Kai Christian Junge, Kieran Daniel Gilday, Cheng Pan

Learning manipulation from demonstration is a key way for humans to teach complex tasks. However, this domain mainly focuses on kinetic teaching, and does not consider imitation of interaction forces which is essential for more contact rich tasks. We propo ...

Institute of Electrical and Electronics Engineers Inc.2024

Tree diversity reduces variability in sapling survival under drought

Jingjing Liang, Charlotte Grossiord

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantatio ...

Wiley2024

From roots to canopy: Unraveling the influence of species diversity on tree water relations under warmer and drier climates

Eugénie Isabelle Mas

The worsening of drought events with rising air temperature alters tree water relations causing severe hydraulic impairments and widespread forest mortality. Mixing tree species with contrasting hydraulic traits could reduce forest vulnerability to extreme ...

EPFL2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Manuel Monteiro Lança Madeira, Pascal Frossard, Ntorina Thanou

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

Springer International Publishing Ag2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

Georg Michael Joachim Starke

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

2023

Perspective Aware Road Obstacle Detection

Pascal Fua, Mathieu Salzmann, Sina Honari, Krzysztof Maciej Lis

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

2023

Social media and deep learning reveal specific cultural preferences for biodiversity

Devis Tuia

Social media has created new opportunities to map cultural ecosystem services (CES) related to biodiversity at large scales. However, using these novel data to understand people's preferences in relation to these CES remains a challenge. To address this, w ...

2023

Interpretable Representation Learning and Evaluation for Abstractive Summarization

Andreas Thomas Marfurt

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

EPFL2023

A landmark environmental law looks ahead

Devis Tuia

In late December 1973, the United States enacted what some would come to call “the pitbull of environmental laws.” In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, ob ...

American Association for the Advancement of Science2023

Fish Diversity in Relation to Littoral Habitats in Three Basins of Lake Kivu (East Africa)

Alfred Johny Wüest

In total, 28 of the 29 fish species reported from the Lake Kivu basin occur in the littoral zone of the lake, but information about their structure, occurrence, and the habitats affecting their distribution is largely lacking. The lake's inshore area is po ...

MDPI2023

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Devis Tuia, Benjamin Alexander Kellenberger

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...

2023

Mechanism balancing taxonomy

Simon Nessim Henein, Hubert Pierre-Marie Benoît Schneegans, Florent Cosandier

The balancing of mechanisms consists in distributing their moving masses, inertias, and elastic components in order to achieve key mechanical properties, such as the elimination of the shaking forces and moments exported onto their supporting structure or ...

2023

Evaluation of genetic demultiplexing of single-cell sequencing data from model species

Clement Helsens

Single-cell sequencing (sc-seq) provides a species agnostic tool to study cellular processes. However, these technologies are expensive and require sufficient cell quantities and biological replicates to avoid artifactual results. An option to address thes ...

LIFE SCIENCE ALLIANCE LLC2023

Different responses of mice and rats hippocampus CA1 pyramidal neurons to in vitro and in vivo-like inputs

Ying Shi, Armando Romani, Maurizio Ferdinando Pezzoli

The fundamental role of any neuron within a network is to transform complex spatiotemporal synaptic input patterns into individual output spikes. These spikes, in turn, act as inputs for other neurons in the network. Neurons must execute this function acro ...

2023

Chronic warming and dry soils limit carbon uptake and growth despite a longer growing season in beech and oak

Charlotte Grossiord, Margaux Clara Lou Didion-Gency

Progressively warmer and drier climatic conditions impact tree phenology and carbon cycling with large consequences for forest carbon balance. However, it remains unclear how individual impacts of warming and drier soils differ from their combined effects ...

Oxford Univ Press Inc2023