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Related publications (30)

Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN

Analysis of single-cell datasets generated from diverse organisms offers unprecedented opportunities to unravel fundamental evolutionary processes of conservation and diversification of cell types. However, interspecies genomic differences limit the joint ...

Nature Portfolio2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

A Gapless Post-quantum Hash Proof System in the Hamming Metric

Serge Vaudenay, Bénédikt Minh Dang Tran

A hash proof system (HPS) is a form of implicit proof of membership to a language. Out of the very few existing post-quantum HPS, most are based on languages of ciphertexts of code-based or lattice-based cryptosystems and inherently suffer from a gap cause ...

2023

Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A of derived brain volume measurements

Tobias Kober, Tom Hilbert, Gian Franco Piredda

Purpose: T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a ...

ELSEVIER SCI LTD2022

Metric learning for kernel ridge regression: assessment of molecular similarity

Friedrich Eisenbrand, Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Raimon Fabregat I De Aguilar-Amat

Supervised and unsupervised kernel-based algorithms widely used in the physical sciences depend upon the notion of similarity. Their reliance on pre-defined distance metrics-e.g. the Euclidean or Manhattan distance-are problematic especially when used in c ...

IOP Publishing Ltd2022

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

We present a discriminative clustering approach in which the feature representation can be learned from data and moreover leverage labeled data. Representation learning can give a similarity-based clustering method the ability to automatically adapt to an ...

2022

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Raimon Fabregat I De Aguilar-Amat

Over the last two decades, data-powered machine learning (ML) tools have profoundly transformed numerous scientific fields. In computational chemistry, machine learning applications have permitted faster predictions of chemical properties and provided powe ...

EPFL2022

fGOT: Graph Distances Based on Filters and Optimal Transport

Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic, Giovanni Chierchia

Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu, Zhigang Li

The current leading 6D object pose estimation methods rely heavily on annotated real data, which is highly costly to acquire. To overcome this, many works have proposed to introduce computer-generated synthetic data. However, bridging the gap between the s ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

Tong Zhang

Visual salient object detection (SOD) aims at finding the salient object(s) that attract human attention, while camouflaged object detection (COD) on the contrary intends to discover the camouflaged object(s) that hidden in the surrounding. In this paper, ...

IEEE COMPUTER SOC2021

Similarity conditions and cube model tests of snow drift and precipitation preferential deposition patterns

Michael Lehning, Borui Zhang, Qingwen Zhang

We explore the process of modeling aeolian snow transport around buildings by proposing a set of similarity requirements on simulating a single snow fall event with drifting. The similarity criteria are used to guide our wind tunnel tests from the particle ...

ELSEVIER2021

CO2-Driven diffusiophoresis and water cleaning: similarity solutions for predicting the exclusion zone in a channel flow

Mrudhula Baskaran

We investigate experimentally and theoretically diffusiophoretic separation of negatively charged particles in a rectangular channel flow, driven by CO2 dissolution from one side-wall. Since the negatively charged particles create an exclusion zone near th ...

ROYAL SOC CHEMISTRY2021

QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval

Shaokai Ye, Yuan He, Hang Su, Jinfeng Li

We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-1 ranked unlabeled images from the database. Compared with que ...

IEEE COMPUTER SOC2021

Pseudomomentum: origins and consequences

Harmeet Singh

The balance of pseudomomentum is discussed and applied to simple elasticity, ideal fluids, and the mechanics of inextensible rods and sheets. A general framework is presented in which the simultaneous variation of an action with respect to position, time, ...

2021

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Hubert Girault, Horst Pick, Natalia Gasilova, Andreas Stephan Lesch, Milica Jovic, Yingdi Zhu, Tzu-En Lin

Skin problems are often overlooked due to a lack of robust and patient-friendly monitoring tools. Herein, we report a rapid, noninvasive, and high-throughput analytical chemical methodology, aiming at real-time monitoring of skin conditions and early detec ...

2021

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI

Tobias Kober, Tom Hilbert, Jérôme Yerly, Ruud van Heeswijk, Elena Najdenovska

Fluorine-19 (F-19) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the ...

WILEY2020

On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

Robert West, Maxime Jean Julien Peyrard, Yang Gao, Wei Zhao

Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual similarity. In this paper, we concern ourselves with reference-free machine trans ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2020

Evolution of Topics and Novelty in Science

Omar Ballester Gonzalez, Orion B Penner

Methods of estimating the similarity between individual publications is an area of long-standing interest in the scientometrics community. Traditional methods have generally relied on references and other metadata, while text mining approaches based on tit ...

INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI2019

Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking

Pascal Fua, Andrii Maksai

Identity Switching remains one of the main difficulties Multiple Object Tracking (MOT) algorithms have to deal with. Many state-of-the-art approaches now use sequence models to solve this problem but their training can be affected by biases that decrease t ...

IEEE2019

Collaborative Filtering Under a Sybil Attack: Similarity Metrics do Matter!

Rachid Guerraoui, Anne-Marie Kermarrec, Antoine Rault, Davide Frey, Florestan Laurentin Marie De Moor

Recommendation systems help users identify interesting content, but they also open new privacy threats. In this paper, we deeply analyze the effect of a Sybil attack that tries to infer information on users from a user-based collaborative-filtering recomme ...

IEEE2018