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Found 10 papers, 2 papers with code
InstructBrush: Learning Attention-based Instruction Optimization for Image Editing
Two key techniques are introduced into InstructBrush, Attention-based Instruction Optimization and Transformation-oriented Instruction Initialization, to address the limitations of the previous method in terms of inversion effects and instruction generalization.
Molecular De Novo Design through Transformer-based Reinforcement Learning
In contrast to the traditional RNN-based models, our proposed method exhibits superior performance in generating compounds predicted to be active against various biological targets, capturing long-term dependencies in the molecular structure sequence.
MIRACLE: Multi-task Learning based Interpretable Regulation of Autoimmune Diseases through Common Latent Epigenetics
DNA methylation is a crucial regulator of gene transcription and has been linked to various diseases, including autoimmune diseases and cancers.
Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation
We demonstrate that domain labels are not directly necessary for BTDA if categorical distributions of various domains are sufficiently aligned even facing the imbalance of domains and the label distribution shift of classes.
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Multi-target Domain Adaptation
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Blended-target Domain Adaptation
Label shift of blended-target domain adaptation
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When Source-Free Domain Adaptation Meets Learning with Noisy Labels
We also prove that such a difference makes existing LLN methods that rely on their distribution assumptions unable to address the label noise in SFDA.
Predicting Li-ion Battery Cycle Life with LSTM RNN
Efficient and accurate remaining useful life prediction is a key factor for reliable and safe usage of lithium-ion batteries.
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation
Second, the overall design space composed of HW/SW partitioning, hardware optimization, and software optimization is huge.
Coordinated Cyber-Attack Detection Model of Cyber-Physical Power System Based on the Operating State Data Link
Existing coordinated cyber-attack detection methods have low detection accuracy and efficiency and poor generalization ability due to difficulties dealing with unbalanced attack data samples, high data dimensionality, and noisy data sets.
Wasserstein Distance Based Domain Adaptation for Object Detection
Prior approaches utilize adversarial training based on cross entropy between the source and target domain distributions to learn a shared feature mapping that minimizes the domain gap.
A Directed Acyclic Graph Approach to Online Log Parsing
A typical log-based system reliability management procedure is to first parse log messages because of their unstructured format; and apply data mining techniques on the parsed logs to obtain critical system behavior information.
Software Engineering
