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09/21/2023
How Robust is Google's Bard to Adversarial Image Attacks?
Multimodal Large Language Models (MLLMs) that integrate text and other m...
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09/05/2023
SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction
Training specific deep learning models for particular tasks is common ac...
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09/04/2023
Memory Efficient Optimizers with 4-bit States
Optimizer states are a major source of memory consumption for training n...
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08/29/2023
Heterogeneous Multi-Task Gaussian Cox Processes
This paper presents a novel extension of multi-task Gaussian Cox process...
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08/29/2023
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence
Continual learning aims to empower artificial intelligence (AI) with str...
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08/21/2023
Towards Accelerated Model Training via Bayesian Data Selection
Mislabeled, duplicated, or biased data in real-world scenarios can lead ...
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06/24/2023
Multi-task multi-station earthquake monitoring: An all-in-one seismic Phase picking, Location, and Association Network (PLAN)
Earthquake monitoring is vital for understanding the physics of earthqua...
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06/21/2023
Training Transformers with 4-bit Integers
Quantizing the activation, weight, and gradient to 4-bit is promising to...
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06/18/2023
Stabilizing GANs' Training with Brownian Motion Controller
The training process of generative adversarial networks (GANs) is unstab...
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06/15/2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
While significant progress has been made on Physics-Informed Neural Netw...
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06/05/2023
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks
Physics-informed Neural Networks (PINNs) have recently achieved remarkab...
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05/30/2023
An absolutely convergent fixed-point fast sweeping WENO method on triangular meshes for steady state of hyperbolic conservation laws
High order fast sweeping methods for efficiently solving steady state so...
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05/30/2023
Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models
Large pre-trained language models (PLMs) have demonstrated strong perfor...
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05/30/2023
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
The neural operator has emerged as a powerful tool in learning mappings ...
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05/28/2023
Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness
Recent works found that deep neural networks (DNNs) can be fooled by adv...
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05/26/2023
ControlVideo: Adding Conditional Control for One Shot Text-to-Video Editing
In this paper, we present ControlVideo, a novel method for text-driven v...
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05/25/2023
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
Score distillation sampling (SDS) has shown great promise in text-to-3D ...
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05/24/2023
Robust Classification via a Single Diffusion Model
Recently, diffusion models have been successfully applied to improving a...
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05/06/2023
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
Diffusion models have exhibited excellent performance in various domains...
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04/25/2023
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
Guided sampling is a vital approach for applying diffusion models in rea...
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04/20/2023
PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image
We study the 3D-aware image attribute editing problem in this paper, whi...
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04/20/2023
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
Large-scale pre-trained models have achieved remarkable success in a var...
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04/20/2023
Learning CLIP Guided Visual-Text Fusion Transformer for Video-based Pedestrian Attribute Recognition
Existing pedestrian attribute recognition (PAR) algorithms are mainly de...
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04/19/2023
A compact simple HWENO scheme with ADER time discretization for hyperbolic conservation laws I: structured meshes
In this paper, a compact and high order ADER (Arbitrary high order using...
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03/31/2023
A Closer Look at Parameter-Efficient Tuning in Diffusion Models
Large-scale diffusion models like Stable Diffusion are powerful and find...
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03/28/2023
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition
Face recognition is a prevailing authentication solution in numerous bio...
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03/20/2023
Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving
3D object detection is an important task in autonomous driving to percei...
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03/16/2023
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
Deep learning models are vulnerable to adversarial examples. Transfer-ba...
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03/12/2023
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale
This paper proposes a unified diffusion framework (dubbed UniDiffuser) t...
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03/09/2023
Reward Informed Dreamer for Task Generalization in Reinforcement Learning
A long-standing goal of reinforcement learning is that algorithms can le...
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03/06/2023
Dual Feedback Attention Framework via Boundary-Aware Auxiliary and Progressive Semantic Optimization for Salient Object Detection in Optical Remote Sensing Imagery
Salient object detection in optical remote sensing image (ORSI-SOD) has ...
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03/02/2023
Model-based Constrained MDP for Budget Allocation in Sequential Incentive Marketing
Sequential incentive marketing is an important approach for online busin...
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02/28/2023
GNOT: A General Neural Operator Transformer for Operator Learning
Learning partial differential equations' (PDEs) solution operators is an...
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02/21/2023
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
We propose a three-stage training strategy called dual pseudo training (...
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02/10/2023
Confidence-based Reliable Learning under Dual Noises
Deep neural networks (DNNs) have achieved remarkable success in a variet...
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02/05/2023
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
A large-scale deep model pre-trained on massive labeled or unlabeled dat...
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01/31/2023
A Comprehensive Survey of Continual Learning: Theory, Method and Application
To cope with real-world dynamics, an intelligent agent needs to incremen...
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01/10/2023
Semiparametric Regression for Spatial Data via Deep Learning
In this work, we propose a deep learning-based method to perform semipar...
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12/01/2022
Why Are Conditional Generative Models Better Than Unconditional Ones?
Extensive empirical evidence demonstrates that conditional generative mo...
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11/15/2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications
Recent advances of data-driven machine learning have revolutionized fiel...
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11/02/2022
DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
Diffusion probabilistic models (DPMs) have achieved impressive success i...
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11/02/2022
Improving transferability of 3D adversarial attacks with scale and shear transformations
Previous work has shown that 3D point cloud classifiers can be vulnerabl...
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11/02/2022
Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network
Model-based reinforcement learning usually suffers from a high sample co...
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10/29/2022
Spectral Representation Learning for Conditional Moment Models
Many problems in causal inference and economics can be formulated in the...
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10/27/2022
Isometric 3D Adversarial Examples in the Physical World
3D deep learning models are shown to be as vulnerable to adversarial exa...
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10/23/2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Laplace approximation (LA) and its linearized variant (LLA) enable effor...
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10/08/2022
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
Recent studies have demonstrated that visual recognition models lack rob...
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10/06/2022
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs
We present a unified hard-constraint framework for solving geometrically...
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09/30/2022
Equivariant Energy-Guided SDE for Inverse Molecular Design
Inverse molecular design is critical in material science and drug discov...
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09/30/2022
