From Automated Bootstrapping to Collaborative Editing: A Framework for 4D City Reconstruction

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Augmenting large language models with chemistry tools

Philippe Schwaller, Oliver Tobias Schilter, Andres Camilo Marulanda Bran, Carlo Baldassari

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Moahan Murugappan

Using the GKEngine code which simulates an electrostatic plasma with adiabatic electron response under a sheared-slab geometry, an attempt at developing a hybrid approach between the delta-f and full-f schemes to describe plasma profiles exhibiting high fl ...

EPFL2024

Accurate and agile flight with winged drones

Valentin Wüest

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

EPFL2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Yuchen Yang

Situated in the intersection of audiovisual archives, computational methods, and immersive interactions, this work probes the increasingly important accessibility issues from a two-fold approach. Firstly, the work proposes an ontological data model to hand ...

ACM2023

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Zhuoqian Yang, Siyuan Li

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...

Ieee Computer Soc2023

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Michaël Unser

We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

IEEE2023

The science of soft robot design: A review of motivations, methods and enabling technologies

Josephine Anna Eleanor Hughes, Francesco Stella

Novel technologies, fabrication methods, controllers and computational methods are rapidly advancing the capabilities of soft robotics. This is creating the need for design techniques and methodologies that are suited for the multi-disciplinary nature of s ...

FRONTIERS MEDIA SA2023

Exploring Novel Modalities for Optical Diffraction Tomography

Amirhossein Saba Shirvan

In the past decade, optical diffraction tomography has gained a lot of attention for its ability to create label-free three-dimensional (3D) images of the refractive index distribution of biological samples using scattered fields measured through holograph ...

EPFL2023

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