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Related publications (103)
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 ...
Berlin2024Compressed 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 LTD2022Metric learning for kernel ridge regression: assessment of molecular similarity
Friedrich Eisenbrand, 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 Ltd2022Discriminative 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 ...
2022Kernel 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 ...
EPFL2022SD-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 INTELLIGENCE2021Uncertainty-aware Joint Salient Object and Camouflaged Object Detection
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 SOC2021Similarity 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 ...
ELSEVIER2021QAIR: 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 SOC2021Pseudomomentum: origins and consequences
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