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Sanghani Center for Artificial Intelligence and Data Analytics
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2021
Natural Language Processing Advancements By Deep Learning: A Survey
Human Apprenticeship Learning via Kernel-based Inverse Reinforcement Learning
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19
Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications
Detecting Anomalies Through Contrast in Heterogeneous Data
Using AntiPatterns to avoid MLOps Mistakes
DeepSI: Interactive Deep Learning for Semantic Interaction
Sensemaking Strategies with Immersive Space to Think
Do we still need physical monitors? An evaluation of the usability of AR virtual monitors for productivity work
CrowdTrace: Visualizing Provenance in Distributed Sensemaking
Deep Graph Learning for Circuit Deobfuscation
RISECURE: Metro Incidents And Threat Detection Using Social Media
SOSNet: A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations
On Parallel Real-Time Security Improvement Using Mixed-Integer Programming
Multiobjective Optimization of the Variability of the High-Performance Linpack Solver
Multi-Level Generative Chaotic Recurrent Network for Image Inpainting
AgroSeek: A system for computational analysis of environmental metagenomic data and associated metadata
The balanced truncation bound is tight for SISO systems when the truncated system is state-space symmetric
Expertise-Aware Truth Analysis and Task Allocation in Mobile Crowdsourcing
Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction
Extracting Temporal Event Relation with Syntactic-Guided Temporal Graph Transformer
AdaReNet: Adaptive Reweighted Semi-supervised Active Learning to Accelerate Label Acquisition
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
ScanBank: A Benchmark Dataset for Figure Extraction from Scanned Electronic Theses and Dissertations
Automatic Metadata Extraction Incorporating Visual Features from Scanned Electronic Theses and Dissertations
On the Evaluation of Generative Adversarial Networks By Discriminative Models
Aspect Classification for Legal Depositions
Bridging cognitive gaps between user and model in interactive dimension reduction
Predicting Stock Price Movement Using Financial News Sentiment
Singular Perturbation-based Reinforcement Learning of Two-Point Boundary Optimal Control Systems
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
Welcome to AI matters 6(2)
Welcome to AI Matters 6(1)
SIGAI annual report: July 1 2019 - June 30 2020
Welcome to AI matters 6(3)
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling
Biodiversity Image Quality Metadata Augments Convolutional Neural Network Classification of Fish Species
CoPhy-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach
GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization
Stability-Based Analysis and Defense against Backdoor Attacks on Edge Computing Services
Improving Robustness to Model Inversion Attacks via Mutual Information Regularization
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective
One-Round Active Learning
A Unified Framework for Task-Driven Data Quality Management
Learnability of Learning Performance and Its Application to Data Valuation
Zero-Round Active Learning
D2P-Fed: Differentially Private Federated Learning With Efficient Communication
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection
Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction
Corpus-level and Concept-based Explanations for Interpretable Document Classification
Deliberate Self-Attention Network with Uncertainty Estimation for Multi-Aspect Review Rating Prediction
DropLoss for Long-Tail Instance Segmentation
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Hybrid Neural Fusion for Full-frame Video Stabilization
Learning Representational Invariances for Data-Efficient Action Recognition
Dynamic View Synthesis from Dynamic Monocular Video
Learning to See Through Obstructions with Layered Decomposition
Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors
Space-time Neural Irradiance Fields for Free-Viewpoint Video
Robust Consistent Video Depth Estimation
Portrait Neural Radiance Fields from a Single Image
Workshop on Data-Efficient Machine Learning (DeMaL)
Self-supervised Transformer for Multivariate Clinical Time-Series with Missing Values
Fair Representation Learning using Interpolation Enabled Disentanglement
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes
Supervised Contrastive Learning for Interpretable Long Document Comparison
Welcome to AI Matters 7(1)
Physics-Guided AI for Large-Scale Spatiotemporal Data
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning
Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation
Chest ImaGenome Dataset for Clinical Reasoning
SAUCE: Truncated Sparse Document Signature Bit-Vectors for Fast Web-Scale Corpus Expansion
SWITCHES: Searchable Web Interface for Topologies of CHEmical Switches
Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning
Hybrid Neural Fusion for Full-frame Video Stabilization
Pose with Style: Detail-Preserving Pose-Guided Image Synthesis with Conditional StyleGAN
Welcome to AI Matters 7(2)
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning
How Knowledge Graph and Attention Help? A Quantitative Analysis into Bag-level Relation Extraction
Selective Differential Privacy for Language Modeling
Aura: Privacy-preserving augmentation to improve test set diversity in noise suppression applications
Traces of Time through Space: Advantages of Creating Complex Canvases in Collaborative Meetings
Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing
DIGDUG: Scalable Separable Dense Graph Pruning and Join Operations in MapReduce
Reducing Noise Pixels and Metric Bias in Semantic Inpainting on Segmentation Map
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation
MetaMLP: A Fast Word Embedding Based Classifier to Profile Target Gene Databases in Metagenomic Samples
A Graph Convolutional Neural Network Based Approach for Traffic Monitoring Using Augmented Detections with Optical Flow
Two-Stage Clustering of Household Electricity Load Shapes for Improved Temporal Pattern Representation
Zero-shot Relation Classification from Side Information
Multi-stage Hybrid Attentive Networks for Knowledge-Driven Stock Movement Prediction
Prompt-based Zero-shot Relation Classification with Semantic Knowledge Augmentation
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding
Online and Distributed Robust Regressions with Extremely Noisy Labels
Semantic Explanation of Interactive Dimensionality Reduction
Narrative Sensemaking: Strategies for Narrative Maps Construction
Design guidelines for narrative maps in sensemaking tasks
Context Integrated Relational Spatio-Temporal Resource Forecasting
COCO-Bridge: Structural Detail Data Set for Bridge Inspections
Analysis of GMRES for Low-Rank and Small-Norm Perturbations of the Identity Matrix
Deep Learning-based Anomaly Detection in Cyber-physical Systems: Progress and Opportunities
From Theory to Code: Identifying Logical Flaws in Cryptographic Implementations in C/C++
Depth and persistence: what researchers need to know about impostor syndrome
ACSAC 2020: Furthering the Quest to Tackle Hard Problems and Find Practical Solutions
Exploitation Techniques for Data-oriented Attacks with Existing and Potential Defense Approaches
Measurable and Deployable Security: Gaps, Successes, and Opportunities
Measurement of Local Differential Privacy Techniques for IoT-based Streaming Data
Tutorial: Investigating Advanced Exploits for System Security Assurance
Data-Driven Vulnerability Detection and Repair in Java Code
Embedding Code Contexts for Cryptographic API Suggestion: New Methodologies and Comparisons
Privacy Guarantees of BLE Contact Tracing: A Case Study on COVIDWISE
Industrial Experience of Finding Cryptographic Vulnerabilities in Large-scale Codebases
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
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