Check computer science papers: citations, claims and retractions

Publication guidelines and recommendations for pupillary measurement in psychophysiological studies

Steinhauer, S. R., Bradley, M. M., Siegle, G. J., Roecklein, K. A., & Dix, A. (2022) · Psychophysiology

Gaze Tracking and Assistive TechnologyHeart Rate Variability and Autonomic Control

Cited by 137

Variational Inference for Infinite Mixtures of Gaussian Processes With Applications to Traffic Flow Prediction

Sun, S., & Xu, X. (2011) · IEEE Transactions on Intelligent Transportation Systems

Gaussian Processes and Bayesian InferenceBayesian Methods and Mixture Models

Cited by 137

Towards multimodal emotion recognition in e-learning environments

Bahreini, K., Nadolski, R., & Westera, W. (2016) · Interactive Learning Environments

Emotion and Mood RecognitionIntelligent Tutoring Systems and Adaptive Learning

Cited by 137

Renewable energy will not solve Bitcoin’s sustainability problem

de Vries, A. (2019) · Joule

Blockchain Technology Applications and SecurityGreen IT and Sustainability

Cited by 137

Predicting Defective Lines Using a Model-Agnostic Technique

Wattanakriengkrai, S., Thongtanunam, P., Tantithamthavorn, C., Hata, H., & Matsumoto, K. (2022) · IEEE Transactions on Software Engineering

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 137

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

Amgad, M., Hodge, J. M., Elsebaie, M. A. T., Bodelon, C., Puvanesarajah, S., Gutman, D. A., Siziopikou, K. P., Goldstein, J. A., Gaudet, M. M., Teras, L. R., et al. (2024) · Nature Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 137

Formalizing Neurath’s ship: approximate algorithms for online causal learning.

Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (2017) · Psychological Review

Bayesian Modeling and Causal InferencePhilosophy of Biology and Scientific Explanation

Cited by 136

Predictive Analytics for Complex IoT Data Streams

Akbar, A., Khan, A., Carrez, F., & Moessner, K. (2017) · IEEE Internet of Things Journal

Advanced Database Systems and QueriesData Stream Mining Techniques

Cited by 136

Two-Step Quantization for Low-bit Neural Networks

Wang, P., Hu, Q., Zhang, Y., Zhang, C., Liu, Y., & Cheng, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 136

Real-time eye gaze tracking with an unmodified commodity webcam employing a neural network

Sewell, W., & Komogortsev, O. (2010) · CHI '10 Extended Abstracts on Human Factors in Computing Systems

Gaze Tracking and Assistive TechnologyEEG and Brain-Computer Interfaces

Cited by 136

Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data

Wand, M., Adams, B., Ovsjanikov, M., Berner, A., Bokeloh, M., Jenke, P., Guibas, L., Seidel, H.-P., & Schilling, A. (2009) · ACM Transactions on Graphics

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 136

Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients

Tsai, P.-C., Lee, T.-H., Kuo, K.-C., Su, F.-Y., Lee, T.-L. M., Marostica, E., Ugai, T., Zhao, M., Lau, M. C., Väyrynen, J. P., et al. (2023) · Nature Communications

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 136

Designing Trans Technology: Defining Challenges and Envisioning Community-Centered Solutions

Haimson, O. L., Gorrell, D., Starks, D. L., & Weinger, Z. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionLGBTQ Health, Identity, and Policy

Cited by 136

Unsupervised Performance Evaluation of Image Segmentation

Chabrier, S., Emile, B., Rosenberger, C., & Laurent, H. (2006) · EURASIP Journal on Advances in Signal Processing

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 136

An attention‐based category‐aware GRU model for the next POI recommendation

Liu, Y., Pei, A., Wang, F., Yang, Y., Zhang, X., Wang, H., Dai, H., Qi, L., & Ma, R. (2021) · International Journal of Intelligent Systems

Recommender Systems and TechniquesHuman Mobility and Location-Based Analysis

Cited by 136

Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning

Deng, Y., Li, Y., Sun, F., Ding, B., & Lam, W. (2021) · Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 136

A-Wristocracy: Deep learning on wrist-worn sensing for recognition of user complex activities

Vepakomma, P., De, D., Das, S. K., & Bhansali, S. (2015) · 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

Context-Aware Activity Recognition SystemsHand Gesture Recognition Systems

Cited by 136

Artificial intelligence explainability: the technical and ethical dimensions

McDermid, J. A., Jia, Y., Porter, Z., & Habli, I. (2021) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 136

The reddots data collection for speaker recognition

Lee, K. A., Larcher, A., Wang, G., Kenny, P., Brümmer, N., Leeuwen, D. V., Aronowitz, H., Kockmann, M., Vaquero, C., Ma, B., et al. (2015) · Interspeech 2015

Speech Recognition and SynthesisPhonetics and Phonology Research

Cited by 136

Select, Answer and Explain: Interpretable Multi-Hop Reading Comprehension over Multiple Documents

Tu, M., Huang, K., Wang, G., Huang, J., He, X., & Zhou, B. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Topic ModelingInformation Retrieval and Search Behavior

Cited by 136

Rearranging the Familiar: Testing Compositional Generalization in Recurrent Networks

Loula, J., Baroni, M., & Lake, B. (2018) · Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP

Topic ModelingNatural Language Processing Techniques

Cited by 136

Impact and Key Challenges of Insider Threats on Organizations and Critical Businesses

Saxena, N., Hayes, E., Bertino, E., Ojo, P., Choo, K.-K. R., & Burnap, P. (2020) · Electronics

Information and Cyber SecurityNetwork Security and Intrusion Detection

Cited by 136

Google in a Quantum Network

Paparo, G. D., & Martin-Delgado, M. A. (2012) · Scientific Reports

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 136

Structured Pruning Learns Compact and Accurate Models

Xia, M., Zhong, Z., & Chen, D. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Advanced Neural Network ApplicationsTopic Modeling

Cited by 136