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08/24/2023
Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Vision-language pre-training models (VLP) are vulnerable, especially to ...
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08/19/2023
BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions
Vision Language Models (VLMs), which extend Large Language Models (LLM) ...
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07/21/2023
Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields
Despite the tremendous progress in neural radiance fields (NeRF), we sti...
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05/30/2023
Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting
Long-term time series forecasting (LTSF) is a crucial aspect of modern s...
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03/23/2023
Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation
In recommendation systems, a large portion of the ratings are missing du...
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10/05/2022
TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning
Electrical energy is essential in today's society. Accurate electrical l...
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01/29/2022
Scale-arbitrary Invertible Image Downscaling
Downscaling is indispensable when distributing high-resolution (HR) imag...
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07/16/2021
Conditional Directed Graph Convolution for 3D Human Pose Estimation
Graph convolutional networks have significantly improved 3D human pose e...
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06/24/2021
Sparse Needlets for Lighting Estimation with Spherical Transport Loss
Accurate lighting estimation is challenging yet critical to many compute...
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06/02/2021
KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients
Partial differential equations (PDEs) fitting scientific data can repres...
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05/18/2021
Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection
In real-world maintenance applications, deep generative models have show...
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03/28/2021
Accurate and Reliable Forecasting using Stochastic Differential Equations
It is critical yet challenging for deep learning models to properly char...
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03/26/2021
Bidirectional Projection Network for Cross Dimension Scene Understanding
2D image representations are in regular grids and can be processed effic...
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12/16/2020
Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting
Time series forecasting is an important yet challenging task. Though dee...
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09/03/2020
Mononizing Binocular Videos
This paper presents the idea ofmono-nizingbinocular videos and a frame-w...
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06/18/2020
Calibrated Reliable Regression using Maximum Mean Discrepancy
Accurate quantification of uncertainty is crucial for real-world applica...
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06/14/2020
Dynamic Window-level Granger Causality of Multi-channel Time Series
Granger causality method analyzes the time series causalities without bu...
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05/10/2019
DEMC: A Deep Dual-Encoder Network for Denoising Monte Carlo Rendering
In this paper, we present DEMC, a deep Dual-Encoder network to remove Mo...
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07/01/2017
SAM: Semantic Attribute Modulation for Language Modeling and Style Variation
This paper presents a Semantic Attribute Modulation (SAM) for language m...
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04/27/2015
Fast Sampling for Bayesian Max-Margin Models
Bayesian max-margin models have shown superiority in various practical a...
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11/24/2014