2025
Joint modeling of degradation signals and time-to-event data for the prediction of remaining useful life.
Qual. Reliab. Eng. Int., March, 2025
Stable-SCore: A Stable Registration-based Framework for 3D Shape Correspondence.
CoRR, March, 2025
Multimodal mixing convolutional neural network and transformer for Alzheimer's disease recognition.
Expert Syst. Appl., 2025
2024
Surface Reconstruction From Point Clouds: A Survey and a Benchmark.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024
Design and Analysis of a Cardioid Flow Tube Valveless Piezoelectric Pump for Medical Applications.
Sensors, 2024
EditScout: Locating Forged Regions from Diffusion-based Edited Images with Multimodal LLM.
CoRR, 2024
Efficient Vision-Language Models by Summarizing Visual Tokens into Compact Registers.
CoRR, 2024
GenQA: Generating Millions of Instructions from a Handful of Prompts.
CoRR, 2024
Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization.
CoRR, 2024
Coercing LLMs to do and reveal (almost) anything.
CoRR, 2024
Benchmarking the Robustness of Image Watermarks.
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CoRR, 2024
Multi-modal learning for inpatient length of stay prediction.
Comput. Biol. Medicine, 2024
M3T-LM: A multi-modal multi-task learning model for jointly predicting patient length of stay and mortality.
Comput. Biol. Medicine, 2024
Toward Intuitive 3D Interactions in Virtual Reality: A Deep Learning- Based Dual-Hand Gesture Recognition Approach.
IEEE Access, 2024
Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers.
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Proceedings of the International Conference for High Performance Computing, 2024
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs.
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
WAVES: Benchmarking the Robustness of Image Watermarks.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
Detecting, Explaining, and Mitigating Memorization in Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
On the Reliability of Watermarks for Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
NEFTune: Noisy Embeddings Improve Instruction Finetuning.
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Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
A deep learning approach for inpatient length of stay and mortality prediction.
J. Biomed. Informatics, November, 2023
Machine learning techniques for stock price prediction and graphic signal recognition.
Eng. Appl. Artif. Intell., May, 2023
Multiscale Attention Networks for Pavement Defect Detection.
IEEE Trans. Instrum. Meas., 2023
Baseline Defenses for Adversarial Attacks Against Aligned Language Models.
CoRR, 2023
Bring Your Own Data! Self-Supervised Evaluation for Large Language Models.
CoRR, 2023
Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust.
CoRR, 2023
Weakly-supervised learning method for the recognition of potato leaf diseases.
Artif. Intell. Rev., 2023
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A Watermark for Large Language Models.
Proceedings of the International Conference on Machine Learning, 2023
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Seeing in Words: Learning to Classify through Language Bottlenecks.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Geometry-Aware Generation of Adversarial Point Clouds.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning.
CoRR, 2022
A deep learning-based approach to extraction of filler morphology in SEM images with the application of automated quality inspection.
Artif. Intell. Eng. Des. Anal. Manuf., 2022
Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors and Machine Learning Algorithms.
IEEE Access, 2022
MtCut: A Multi-Task Framework for Ranked List Truncation.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification.
Proceedings of the International Conference on Machine Learning, 2022
2021
A Neural Network-Based Joint Prognostic Model for Data Fusion and Remaining Useful Life Prediction.
IEEE Trans. Neural Networks Learn. Syst., 2021
Orthogonal Deep Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2021
Machine Learning based Medical Image Deepfake Detection: A Comparative Study.
CoRR, 2021
Sign-Agnostic Implicit Learning of Surface Self-Similarities for Shape Modeling and Reconstruction From Raw Point Clouds.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Deep Optimized Priors for 3D Shape Modeling and Reconstruction.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
Performance Evaluation of Probabilistic Methods Based on Bootstrap and Quantile Regression to Quantify PV Power Point Forecast Uncertainty.
IEEE Trans. Neural Networks Learn. Syst., 2020
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Multiple-Change-Point Modeling and Exact Bayesian Inference of Degradation Signal for Prognostic Improvement.
IEEE Trans Autom. Sci. Eng., 2019
Geometry-aware Generation of Adversarial and Cooperative Point Clouds.
CoRR, 2019
Learning to Discover Curbside Parking Spaces from Vehicle Trajectories.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019
2018
Degradation modeling and RUL prediction using Wiener process subject to multiple change points and unit heterogeneity.
Reliab. Eng. Syst. Saf., 2018
2017
Multiple-Phase Modeling of Degradation Signal for Condition Monitoring and Remaining Useful Life Prediction.
IEEE Trans. Reliab., 2017