Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning

Predictions made by deep learning models are prone to data perturbations, adversarial attacks, and out-of-distribution inputs. To build a trusted AI system, it is therefore critical to accurately quantify the prediction uncertainties. While current efforts focus on improving uncertainty quantification accuracy and efficiency, there is a need to identify uncertainty sources and take actions to mitigate their effects on predictions. Therefore, we propose to develop explainable and actionable Bayesian deep learning methods to not only perform accurate uncertainty quantification but also explain the uncertainties, identify their sources, and propose strategies to mitigate the uncertainty impacts. Specifically, we introduce a gradient-based uncertainty attribution method to identify the most problematic regions of the input that contribute to the prediction uncertainty. Compared to existing methods, the proposed UA-Backprop has competitive accuracy, relaxed assumptions, and high efficiency. Moreover, we propose an uncertainty mitigation strategy that leverages the attribution results as attention to further improve the model performance. Both qualitative and quantitative evaluations are conducted to demonstrate the effectiveness of our proposed methods.Comment: Accepted to CVPR 202

Moneyball:Analyzing the Efficiency of English Premier League Strikers Using Data Envelopment Analysis

In the spirit of the ‘moneyball’ paradigm, this study introduces the Player Performance Efficiency Index (PEI), designed for English Premier League football players, using an advanced Data Envelopment Analysis (DEA) framework. Our study improves upon traditional DEA models by adding relative weight constraints, positive weight attributions, and cross-efficiency considerations, proposing an index that closely mirrors real-world conditions and aligns with expert opinions. The PEI objectively evaluates players across four key technical dimensions: (i) goal-scoring, (ii) creative playmaking, (iii) dribbling, and (iv) defense. It serves as a valuable decision-making tool for club management, coaches, and players. Empirical findings from our study show a strong correlation between player efficiency and team success, particularly in goal-scoring and playmaking. The PEI enhances existing performance metrics, offering a more comprehensive, objective assessment of player performance

Finding groups of people in Google news

In this paper, we study the problem of content-based social network discovery among people who frequently appear in world news. Google news is used as the source of data. We describe a probabilistic framework for associating people with groups. A low-dimensional topic-based representation is first obtained for news stories via probabilistic latent semantic analysis (PLSA). This is followed by construction of semantic groups by clustering such representations. Unlike many existing social network analysis approaches, which discover groups based only on binary relations (e.g. co-occurrence of people in a news article), our model clusters people using their topic distribution, which introduces contextual information in the group formation process (e.g. some people belong to several groups depending on the specific subject). The model has been used to study evolution of people with respect to topics over time. We also illustrate the advantages of our approach over a simple co-occurrence-based social network extraction method

Finding groups of people in Google news

In this paper, we study the problem of content-based social network discovery among people who frequently appear in world news. Google news is used as the source of data. We describe a probabilistic framework for associating people with groups. A low-dimensional topic-based representation is first obtained for news stories via probabilistic latent semantic analysis (PLSA). This is followed by construction of semantic groups by clustering such representations. Unlike many existing social network analysis approaches, which discover groups based only on binary relations (e.g. co-occurrence of people in a news article), our model clusters people using their topic distribution, which introduces contextual information in the group formation process (e.g. some people belong to several groups depending on the specific subject). The model has been used to study evolution of people with respect to topics over time. We also illustrate the advantages of our approach over a simple co-occurrence-based social network extraction method

Potential of Novel EPO Derivatives in Limb Ischemia

Erythropoietin (EPO) has tissue-protective properties, but it increases the risk of thromboembolism by raising the haemoglobin concentration. New generation of EPO derivatives is tissue protective without the haematopoietic side effects. Preclinical studies have demonstrated their effectiveness and safety. This paper summarizes the development in EPO derivatives with emphasis on their potential use in critical limb ischaemia

Generation, annotation, and analysis of ESTs from midgut tissue of adult female Anopheles stephensi mosquitoes

<p>Abstract</p> <p>Background</p> <p>Malaria is a tropical disease caused by protozoan parasite, <it>Plasmodium</it>, which is transmitted to humans by various species of female anopheline mosquitoes. <it>Anopheles stephensi </it>is one such major malaria vector in urban parts of the Indian subcontinent. Unlike <it>Anopheles gambiae</it>, an African malaria vector, transcriptome of <it>A. stephensi </it>midgut tissue is less explored. We have therefore carried out generation, annotation, and analysis of expressed sequence tags from sugar-fed and <it>Plasmodium yoelii </it>infected blood-fed (post 24 h) adult female <it>A. stephensi </it>midgut tissue.</p> <p>Results</p> <p>We obtained 7061 and 8306 ESTs from the sugar-fed and <it>P. yoelii </it>infected mosquito midgut tissue libraries, respectively. ESTs from the combined dataset formed 1319 contigs and 2627 singlets, totaling to 3946 unique transcripts. Putative functions were assigned to 1615 (40.9%) transcripts using BLASTX against UniProtKB database. Amongst unannotated transcripts, we identified 1513 putative novel transcripts and 818 potential untranslated regions (UTRs). Statistical comparison of annotated and unannotated ESTs from the two libraries identified 119 differentially regulated genes. Out of 3946 unique transcripts, only 1387 transcripts were mapped on the <it>A. gambiae </it>genome. These also included 189 novel transcripts, which were mapped to the unannotated regions of the genome. The EST data is available as ESTDB at <url>http://mycompdb.bioinfo-portal.cdac.in/cgi-bin/est/index.cgi</url>.</p> <p>Conclusion</p> <p>3946 unique transcripts were successfully identified from the adult female <it>A. stephensi </it>midgut tissue. These data can be used for microarray development for better understanding of vector-parasite relationship and to study differences or similarities with other malaria vectors. Mapping of putative novel transcripts from <it>A. stephensi </it>on the <it>A. gambiae </it>genome proved fruitful in identification and annotation of several genes. Failure of some novel transcripts to map on the <it>A. gambiae </it>genome indicates existence of substantial genomic dissimilarities between these two potent malaria vectors.</p