Exploring Simple Siamese Representation Learning

Siamese networks have become a common structure in various recent models for visual representation learning . These models maximize thesimilarity between two augmentations of one image, subject to certain conditions for avoiding collapsing solutions . Our experiments show thatcollapsing solutions do exist for the loss and structure, but a stop-gradientoperation plays an essential role in preventing collapsing .…

Neural Scene Graphs for Dynamic Scenes

In this work, we present the first neural renderingmethod that decomposes dynamic scenes into scene graphs . We propose a learnedscene graph representation, which encodes object transformation and radiance, to efficiently render novel arrangements and views of the scene . We assessthe proposed method on synthetic and real automotive data, validating that ourapproach learns dynamic scenes – only by observing a video of this scene – andallows for rendering novel photo-realistic views of novel scene compositions with unseen sets of objects at unseen poses .…

Collaborative Storytelling with Large scale Neural Language Models

Storytelling plays a central role in human socializing and entertainment . We present a collaborative storytelling system which works with a human storyteller to create a story by generating new utterances based on the story so far . We constructed the storytelling system by tuning apublicly-available large scale language model on a dataset of writing prompts and their accompanying fictional works .…

Long Short Term Memory Networks for Bandwidth Forecasting in Mobile Broadband Networks under Mobility

Bandwidth forecasting in Mobile Broadband (MBB) networks is a challenging task, particularly when coupled with a degree of mobility . HINDSIGHT++ is an open-source R-based framework for bandwidthforecasting experimentation in MBB networks with Long Short Term Memory (LSTM)networks . The study aims to investigate the impact of hyperparameter optimization on achieving state-of-the-art performance and beyond .…

MobileDepth Efficient Monocular Depth Prediction on Mobile Devices

Depth prediction is fundamental for many useful applications on computervision and robotic systems . On mobile phones, some useful applications such as augmented reality, autofocus and so on could be enhanced by accurate depth prediction . An Android application has been developed which can load CNN models topredict depth map by the monocular images captured from the mobile camera .…

Survey and Open Problems in Privacy Preserving Knowledge Graph Merging Query Representation Completion and Applications

Knowledge Graph (KG) has attracted more and more companies’ attention for itsability to connect different types of data in meaningful ways . However, the data isolation problem limits the performance of KG and prevents its further development . Multiple parties have their own KGs but they cannot share with each other due to regulation or competition reasons .…

Locally Aware Constrained Games on Networks

Network games have been instrumental in understanding strategic behavior of networks for applications such as critical infrastructure networks, social networks, and cyber-physical systems . One critical challenge of network games is that the behaviors of the players are constrained by the underlying physicallaws or safety rules, and the players may not have complete knowledge of network-wide constraints .…

SophiaPop Experiments in Human AI Collaboration on Popular Music

A diverse team of engineers, artists, and algorithms, collaborated to createsongs for SophiaPop, via various neural networks, robotics technologies, andartistic tools . SophiaPop represents a human-AI collaboration, aspiring toward humanAI symbiosis . We believe that such a creative convergence of multipledisciplines with humans and AI working together, can make AI relevant to humanculture in new and exciting ways, and lead to a hopeful vision for the future of human- AI relations .…

Improvement of Classification in One Stage Detector

RetinaNet proposed Focal Loss for classification task and improved one-stagedetectors greatly . Most ofpredicted boxes whose IoU with ground-truth boxes are greater than 0.5, while their classification scores are lower than .5 . Our method can not only improve classification task, but also easemisalignment of classification and localization .…

Hop Constrained Oblivious Routing

We prove the existence of an oblivious routing scheme that is $\mathrm{poly}(\log n)-competitive in terms of $congestion + dilation . The dilation is the maximum path hop-length, the congestion is the number of paths that include any single edge . The routing scheme obliviously and randomly selects a path for each packet independent of (the existence of) the other packets .…

SIMF Single Instruction Multiple Flush Mechanism for Processor Temporal Isolation

Asingle-instruction multiple-flush (SIMF) mechanism to flush the core-level state is used by operating-system-level solutions . SIMF significantly alleviates the overhead offlushing by more than a factor of two in execution time and reduces dynamic instruction count by orders-of-magnitude . The resultant processor isprototyped on Xilinx ZCU102 FPGA and validated with seL4microkernel, Linux kernel in multi-core scenarios, and a cache timing attack attack .…

Born Identity Network Multi way Counterfactual Map Generation to Explain a Classifier s Decision

There exists an apparent negative correlation between performance andinterpretability of deep learning models . We propose Born Identity Network (BIN) which is a post-hocapproach for producing multi-way counterfactual maps . Counterfactual maptransforms an input sample to be classified as a target label, similarto how humans process knowledge through counterfactsual thinking .…

Deep Snapshot HDR Imaging Using Multi Exposure Color Filter Array

In this paper, we propose a deep snapshot high dynamic range (HDR) imaging framework that can effectively reconstruct an HDR image from the RAW datacaptured using a multi-exposure color filter array (ME-CFA) We introduce the idea of luminancenormalization that simultaneously enables effective loss computation and input data normalization by considering relative local contrasts in the”normalized-by-luminance” HDR domain .…

DoDNet Learning to segment multi organ and tumors from multiple partially labeled datasets

A dynamicon-demand network (DoDNet) learns to segment multiple organs and tumors on partially labeled datasets . DoDNet consists of a shared encoder-decoderarchitecture, a task encoding module, a controller for generating dynamicconvolution filters, and a single but dynamic segmentation head . The information of the current segmentation task is encoded as a task-aware priorto tell the model what the model is expected to solve .…

Unbalanced Incomplete Multi view Clustering via the Scheme of View Evolution Weak Views are Meat Strong Views do Eat

Incomplete multi-view clustering is an important technique to deal with real-world data . Different views often have distinct incompleteness, which results in strong views (low-incompleteness views) and weak views (high-incomplete views) The UnbalancedIncomplete Multi-view Clustering method (UIMC) improves the clustering performance by up to 40% on three evaluation metrics over other state-of-the-art methods .…

Planning Folding Motion with Simulation in the Loop Using Laser Forming Origami and Thermal Behaviors as an Example

Recent works have shown success in estimating foldability of adesign using robot motion planners . However, many foldable structures areactuated using physically coupled reactions (i.e., folding originated fromthermal, chemical, or electromagnetic loads) Therefore, a reliable foldabilityanalysis must consider additional constraints that resulted from these criticalphenomena .…

On barren plateaus and cost function locality in variational quantum algorithms

A barren plateau is the phenomenon of exponentiallyvanishing gradients in sufficiently expressive quantum circuits . It has been established that the onset of a barren plateau regime depends on the cost function . Here we derive a lower bound on thevariance of the gradient, which depends mainly on the width of the circuitcausal cone of each term in the Pauli decomposition of a cost function.…

On Error Exponents of Encoder Assisted Communication Systems

We consider a point-to-point communication system, where in addition to theencoder and the decoder, there is a helper that observes non-causally therealization of the noise vector and provides a (lossy) rate-$R$ description of it to the encoder . We study the cases of both fixed-rate and variable-rate noisedescriptions by the helper .…

A Deep Language independent Network to analyze the impact of COVID 19 on the World via Sentiment Analysis

Wuhan experienced an outbreak of novel coronavirus, which soon spread all over the world, resulting in a deadly pandemic that infected millions of people around the globe . We propose a deep language-independent Multilevel Attention-basedConv-BiGRU network (MACBiG-Net), which includes embedding layer, word-levelencoded attention, and sentence-level encoded attention mechanism to extract positive, negative, and neutral sentiments .…

A lightweight cryptography LWC framework to secure memory heap in Internet of Things

Java is the most common platform for embedded applications such as IoT, Wireless Sensors Networks (WSN), Near Field Communications (NFC) and RFID . Object programming languagessuch as Java, SWIFT, PHP and C++ use garbage collection after any object run which creates security loophole for attacks such as Next Memory AddressOccupation (NMAO), memory replay, Learning Tasks Behaviors (LTB) The proposed method prevents directed attack by encrypting the objectGarbage Collection at run time .…

PSD2 Explainable AI Model for Credit Scoring

The aim of this paper is to develop and test advanced analytical methods to improve the prediction accuracy of Credit Risk Models, preserving at the sametime the model interpretability . The project focuses on applying an explainable machine learning model to PSD2-related databases .…

PIFE PIC Parallel Immersed Finite Element Particle In Cell For 3 D Kinetic Simulations of Plasma Material Interactions

PIFE-PIC is a novel three-dimensional (3-D) ParallelImmersed-Finite-Element (IFE) Particle-in-Cell (PIC) simulation model . A simulation of theorbital-motion-limited (OML) sheath of a dielectric sphere immersed in astationary plasma is carried out to validate the code package . A large-scale simulation ofplasma charging at a lunar crater containing 2 million PIC cells (10 millionFE/IFE cells) and about 520 million particles, running for 20,000 PIC steps in about 109 wall-clock hours, is presented to demonstrate the high-performance computing capability of Pife-Pic .…

User and Item aware Estimation of Review Helpfulness

In online review sites, the analysis of user feedback for assessing itshelpfulness for decision-making is usually carried out by studying the properties of individual reviews . We propose a novel helpfulness estimation model that extends previous ones with analysis of deviations in rating, length and polarity with respect to the reviews written by the same person, or concerning the same item .…