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09/14/2023
Beta Diffusion
We introduce beta diffusion, a novel generative modeling method that int...
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07/17/2023
AltFreezing for More General Video Face Forgery Detection
Existing face forgery detection models try to discriminate fake images b...
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06/12/2023
MPPN: Multi-Resolution Periodic Pattern Network For Long-Term Time Series Forecasting
Long-term time series forecasting plays an important role in various rea...
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05/01/2023
In-Context Learning Unlocked for Diffusion Models
We present Prompt Diffusion, a framework for enabling in-context learnin...
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04/28/2023
Optimizing Workflow for Elite Developers: Perspectives on Leveraging SE Bots
Small-scale automation services in Software Engineering, known as SE Bot...
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04/25/2023
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Diffusion models are powerful, but they require a lot of time and data t...
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04/12/2023
SuperpixelGraph: Semi-automatic generation of building footprint through semantic-sensitive superpixel and neural graph networks
Most urban applications necessitate building footprints in the form of c...
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03/16/2023
DIRE for Diffusion-Generated Image Detection
Diffusion models have shown remarkable success in visual synthesis, but ...
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02/28/2023
Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction
Cellular traffic prediction is an indispensable part for intelligent tel...
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12/19/2022
Co-designing for a Hybrid Workplace Experience in Software Development
With increasing demands for flexible work models, many IT organizations ...
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09/13/2022
Towards Efficient Architecture and Algorithms for Sensor Fusion
The safety of an automated vehicle hinges crucially upon the accuracy of...
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08/29/2022
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
The deep neural network (DNN) models are deemed confidential due to thei...
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08/12/2022
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
Offline reinforcement learning (RL), which aims to learn an optimal poli...
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06/14/2022
Probabilistic Conformal Prediction Using Conditional Random Samples
This paper proposes probabilistic conformal prediction (PCP), a predicti...
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06/05/2022
Diffusion-GAN: Training GANs with Diffusion
For stable training of generative adversarial networks (GANs), injecting...
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05/09/2022
Towards a High-performance and Secure Memory System and Architecture for Emerging Applications
In this dissertation, we propose a memory and computing coordinated meth...
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04/19/2022
Network Topology Optimization via Deep Reinforcement Learning
Topology impacts important network performance metrics, including link u...
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03/21/2022
Learning Enriched Illuminants for Cross and Single Sensor Color Constancy
Color constancy aims to restore the constant colors of a scene under dif...
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02/22/2022
Enabling Efficient Deep Convolutional Neural Network-based Sensor Fusion for Autonomous Driving
Autonomous driving demands accurate perception and safe decision-making....
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02/19/2022
A Regularized Implicit Policy for Offline Reinforcement Learning
Offline reinforcement learning enables learning from a fixed dataset, wi...
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06/06/2021
Uformer: A General U-Shaped Transformer for Image Restoration
In this paper, we present Uformer, an effective and efficient Transforme...
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04/08/2021
Cross-status Communication and Project Outcomesin OSS Development A Language Style Matching Perspective
The success of an open source software (OSS) project requires effective ...
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10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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07/13/2020
Implicit Distributional Reinforcement Learning
To improve the sample efficiency of policy-gradient based reinforcement ...
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03/17/2020
Co-Optimizing Performance and Memory FootprintVia Integrated CPU/GPU Memory Management, anImplementation on Autonomous Driving Platform
Cutting-edge embedded system applications, such as self-driving cars and...
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02/21/2020
Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D Reconstruction
Integration of aerial and ground images has been proved as an efficient ...
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12/31/2019
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation
Sequence generation models are commonly refined with reinforcement learn...
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10/30/2019
Thompson Sampling via Local Uncertainty
Thompson sampling is an efficient algorithm for sequential decision maki...
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08/22/2019
