Return migration of German affiliated researchers Analyzing departure and return by gender cohort and discipline using Scopus bibliometric data 1996 2020

The international migration of researchers is a highly prized dimension of scientific mobility and motivates considerable policy debate . In this study, we use Scopus bibliometric data on 8 million publications from 1.1 million researchers who have published at least once with an affiliation address from Germany in 1996-2020 .…

Communicating Patient Health Data A Wicked Problem

Designing patient-collected health data visualizations to support discussing patient data during clinical visits is a challenging problem due to theheterogeneity of the parties involved . Designers must ensure that all parties’ needs are met . This complexity makes it challenging to find a definitive solution that can work forevery individual .…

BPPChecker An SMT based Model Checker on Basic Parallel Processes

Basic Parallel Process (BPP), as a subclass of Petri nets, can be used as a model for describing and verifying concurrent programs with lowercomplexity . We propose and implement BPPChecker, the first model checker forverifying CTL on BPP . For EF operator, we reduce the model checking of EF-formulas to the satisfiabilityproblem of existential Presburger formula .…

Accelerating Genetic Programming using GPUs

Genetic Programming (GP), an evolutionary learning technique, has multiple applications in machine learning such as curve fitting, data modelling, featureselection, classification etc. GP has several inherent parallel steps, making it an ideal candidate for GPU based parallelization . We evaluate our algorithm on synthetic datasets for the PagiePolynomial (ranging in size from $4096$ to $16$ million points) We run performance benchmarks on our algorithmand gplearn, profiling the training time, test accuracy, and loss .…

A Broad Spectrum Diffractive Network via Ensemble Learning

A broad-spectrum diffractive deep neural network (BS-D2NN) incorporates multi-wavelength channels of input lightfields and performs a parallel phase-only modulation . A complementary multi-channel base learner cluster is formed in ahomogeneous ensemble framework based on the diffractive dispersion duringlightwave modulation . The BS-D1NN can be trained usingdeep learning algorithms so as to perform a kind of wavelength-insensitivehigh-accuracy object classification .…

Zipping Strategies and Attribute Grammars

Zippers provide a simple, but generic tree-walk mechanism that is the building blocktechnique we use to express the purely-functional embedding of both techniques . The combined embedding is easier to maintain and extend since it is written in a concise and uniformsetting .…

Optimal Distribution Design for Irregular Repetition Slotted ALOHA with Multi Packet Reception

ALOHA (IRSA) holds a great potential in improving the accesscapacity of massive machine type communication systems . K = 2 (multi-packet reception capability)may be the most suitable scheme for scenarios that allow smaller resourceefficiency in exchange for greater throughput . In this paper, we analyticallyderive an optimal transmission probability distribution for IRSA with K =2 .…

Low rank Matrix Recovery With Unknown Correspondence

We study a matrix recovery problem with unknown correspondence . We show that it is possible to recover $M$ via solving a nuclear normminimization problem . We propose an algorithm,$\text{M}^3\text {O}$ (Matrix recovery via Min-Max Optimization) which recastststhis combinatorial problem as a continuous minimax optimization problem andsolves it by proximal gradient with a Max-Oracle .…

Return migration of German affiliated researchers Analyzing departure and return by gender cohort and discipline using Scopus bibliometric data 1996 2020

The international migration of researchers is a highly prized dimension of scientific mobility and motivates considerable policy debate . In this study, we use Scopus bibliometric data on 8 million publications from 1.1 million researchers who have published at least once with an affiliation address from Germany in 1996-2020 .…

The Pebble Relation Comonad in Finite Model Theory

The pebbling comonad, introduced by Abramsky, Dawar and Wang, provides acategorical interpretation for k-pebble games from finite model theory . The coKleisli category of the pebble-relation comonads specifies equivalences under different fragments and extensions of infinitary k-variable logic . We prove a new Lov\’asz-type theorem relating pathwidth to therestricted conjunction fragment of k- variable logic with counting quantifiers .…

Intent based Product Collections for E commerce using Pretrained Language Models

Building a shopping product collection has been primarily a human job . With the manual efforts of craftsmanship, experts collect related but diverse products with common shopping intent that are effective when displayed together . Automatically constructing a collection requires an ML system to learn a complex relationship between the customer’s intent and the product’sattributes .…

Faster Modular Composition

A new Las Vegas algorithm is presented for the composition of two polynomialsmodulo a third one, over an arbitrary field . When the degrees of thesepolynomials are bounded by $n, the algorithm uses $O(n^{1.43)$ field operations . The previous fastest algebraic algorithms, due to Brent and Kung in 1978, require $ O(n.63) field operations in general, and ${n.3/2+o(1)$ in particular case of power series over a field of large enoughcharacteristic .…

Dynamics of Cross Platform Attention to Retracted Papers Pervasiveness Audience Skepticism and Timing of Retractions

Retracted papers often circulate widely on social media, online news outlets and other websites before their official retraction . The spread of potentiallyinaccurate or misleading results from retracted papers can harm the scientific community and the public . This finding indicates that untrustworthyresearch penetrates even curated platforms and is often shared uncritically,plplifying the negative impact on the public, say the authors .…

Uplink Power Control in Integrated Access and Backhaul Networks

Integrated access and backhaul (IAB) network is a novel radio access network(RAN) solution, enabling network densification for 5G and beyond . We use power control combined with resource allocation algorithms todevelop efficient IAB networks with high service coverage . We also study the effect of different parameters including minimum data raterequirement, coverage distance and transmit power on the network performance .…

New techniques for bounding stabilizer rank

In this work, we present number-theoretic and algebraic-geometric techniques for bounding the stabilizer rank of quantum states . First, we find the first non-trivial examples of quantumstates with multiplicative stabilizer ranks under the tensor product . We also find new bounds on the genericstabilizer rank.…

StreaMulT Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data

This paper tackles the problem of processing and combining efficientlyarbitrary long data streams . Common applications can be, for instance, long-timeindustrial or real-life systems monitoring from multimodal heterogeneous data . To tackle this problem, we propose StreaMulT, a Streaming Multimodal Transformer, relying on cross-modalattention and an augmented memory bank to process arbitrary long inputsequences at training time and run in a streaming way at inference .…

Brittle interpretations The Vulnerability of TCAV and Other Concept based Explainability Tools to Adversarial Attack

Methods for model explainability have become increasingly critical fortesting the fairness and soundness of deep learning . In safety-critical applications, there is need for security around not only the machine learning pipeline but also the modelinterpretation process . We show that by perturbing the examples of the concept that is being investigated, we can radically change the output of the interpretability method, e.g.…

Offline Reinforcement Learning with Soft Behavior Regularization

Most prior approaches to offline reinforcement learning (RL) utilize behavior regularization, typically augmenting existing off-policyactor critic algorithms with a penalty measuring divergence between the policy and the offline data . We propose a practical way to compute the density ratio and demonstrate its equivalence to a state-dependentbehavior regularization .…

Coarse to Fine Video Retrieval before Moment Localization

Current state-of-the-art methods for video corpus moment retrieval (VCMR) often use similarity-based feature alignment approach . However, late fusion methods like cosine similarityalignment are unable to make full use of the information from both query texts and videos . In this paper, we combine feature alignment with feature fusion topromote the performance on VCMR .…

The Neural MMO Platform for Massively Multiagent Research

Neural MMO is a computationally accessible research platform that combines large agent populations, long time horizons, open-ended tasks, and modular gamesystems . We present Neural MMO as free and opensource software with active support, ongoing development, documentation, and training, logging, and visualization tools to help users adapt to the new setting .…

Parallel Algebraic Effect Handlers

Algebraic effects and handlers support composable and structured control-flowabstraction . We formalize an untyped lambdacalculus which models two key features, effect handlers and parallelizablecomputations . We present various interesting examples expressible in our calculus, and provide a Haskell implementation . We hope this paper provides a basis for future designs and implementations of parallel algebraic effect handlers of this type of effect handlers .…

Video based cattle identification and action recognition

Deep learning models have been developed and tested with videos acquired in a farm . An accuracy of 84.4\% has beenachieved for the detection of drinking events, and 94.4% for grazing events . We demonstrate a working prototype for the monitoring of cow welfare by analysing the animal behaviours of individual animals to enableautomated farm provenance .…

DeepSSM A Blueprint for Image to Shape Deep Learning Models

Statistical shape modeling (SSM) characterizes anatomical variations in apopulation of shapes generated from medical images . SSM requires consistentshape representation across samples in shape cohort . Theseshape representations are then used to extract low-dimensional shapedescriptors that facilitate subsequent analyses in different applications .…

Region Semantically Aligned Network for Zero Shot Learning

Zero-shot learning (ZSL) aims to recognize unseen classes based on the knowledge of seen classes . Previous methods focused on learning directembeddings from global features to the semantic space in hope of knowledgetransfer from seen classes to unseen classes . Instead of using globalfeatures which are obtained by an average pooling layer after an image encoder, we directly utilize the output of the image .…

Semi supervised Multi task Learning for Semantics and Depth

Multi-Task Learning (MTL) aims to enhance the model generalization by sharingrepresentations between related tasks for better performance . Typical MTLmethods are jointly trained with the complete multitude of ground-truths forall tasks simultaneously . However, one single dataset may not contain theannotations for each task of interest .…

Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution

In this paper, we introduce a variational Bayesian algorithm (VBA) for imageblind deconvolution . Our generic framework incorporates smoothness priors on the unknown blur/image and possible affine constraints (e.g., sum to one) on the blur kernel . One of our main contributions is the integration of VBA withina neural network paradigm, following an unrolling methodology .…

Compressibility of Distributed Document Representations

We propose CoRe, a straightforward, representation learner-agnostic framework suitable for representation compression . The CoRe’s performance was studied on a collection of 17 real-life corpora from biomedical,news, social media, and literary domains . We explored the behavior whenconsidering contextual and non-contextual document representations, differentcompression levels, and 9 different compression algorithms .…

A more direct and better variant of New Q Newton s method Backtracking for m equations in m variables

In this paper we propose a variant of New Q-Newton’s method Backtracking . The update rule of our method is $x\mapsto x-\gamma (x)w(x)$. Good theoretical guarantees are proven, in particular for systems ofpolynomial equations . In “generic situations”, we will also discuss a way to avoid that the limit of the constructed sequence is a solution of $H(x), but not of $F(x)=0$ The limit is a .…