Single Particle Analysis
25 papers with code • 0 benchmarks • 0 datasets
Single Particle Analysis
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Most implemented papers
Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization
Panxjia/SPA_CVPR2021
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CVPR 2021
Weakly supervised object localization(WSOL) remains an open problem given the deficiency of finding object extent information using a classification network.
Adapted Human Pose: Monocular 3D Human Pose Estimation with Zero Real 3D Pose Data
ostadabbas/adaptedhumanpose
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In this paper, we focus on alleviating the negative effect of domain shift in both appearance and pose space for 3D human pose estimation by presenting our adapted human pose (AHuP) approach.
Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO
While many Particle Swarm Optimization (PSO) algorithms only use fitness to assess the performance of particles, in this work, we adopt Surprisingly Popular Algorithm (SPA) as a complementary metric in addition to fitness.
Smoothed Separable Nonnegative Matrix Factorization
More recently, Bhattacharyya and Kannan (ACM-SIAM Symposium on Discrete Algorithms, 2020) proposed an algorithm for learning a latent simplex (ALLS) that relies on the assumption that there is more than one nearby data point to each vertex.
Ab-initio Contrast Estimation and Denoising of Cryo-EM Images
We show that the contrast variability can be derived from the 2-D covariance matrix and we apply the existing Covariance Wiener Filtering (CWF) framework to estimate it.
Low-complexity Near-optimum Symbol Detection Based on Neural Enhancement of Factor Graphs
In this paper, we develop and evaluate efficient strategies to improve the performance of the factor graph-based symbol detection by means of neural enhancement.
Search to Pass Messages for Temporal Knowledge Graph Completion
striderdu/spa
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In particular, we develop a generalized framework to explore topological and temporal information in TKGs.
Structured Pruning Adapters
lukashedegaard/structured-pruning-adapters
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To improve on this, we propose Structured Pruning Adapters (SPAs), a family of compressing, task-switching network adapters, that accelerate and specialize networks using tiny parameter sets and structured pruning.
Robust Multi-Agent Reinforcement Learning with State Uncertainty
sihongho/robust_marl_with_state_uncertainty
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Then we propose a robust multi-agent Q-learning (RMAQ) algorithm to find such an equilibrium, with convergence guarantees.
A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning
zjukg/comprehensive-study-over-relational-patterns
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Though KGE models' capabilities are analyzed over different relational patterns in theory and a rough connection between better relational patterns modeling and better performance of KGC has been built, a comprehensive quantitative analysis on KGE models over relational patterns remains absent so it is uncertain how the theoretical support of KGE to a relational pattern contributes to the performance of triples associated to such a relational pattern.
