Many multiresolution methods have been developed to capture graph patterns at multiple scales, but most of them depend on predefined and handcrafted multiresolution transforms that remain fixed throughout the training process once formulated. Due to variations in graph instances and distributions, fixed...
Extremely Simple Activation Shaping for Out-of-Distribution Detection |[pdf] A processing‑in‑pixel‑in‑memory paradigm for resource‑constrained TinyML applications |[pdf] [tinySNN]: Towards Memory- and Energy-Efficient Spiking Neural Networks |[pdf] ...
aThe batches and conditions arrangement of count matrices in the simulated datasets. Totally 8 count matrices are generated in each dataset, corresponding to 2 batches and 2 condition types. The matrix with dashed borders is held out in the out-of-sample generalization test.bThe loss values of ...
includingnatural language processing (NLP),speech recognition, image recognition and object detection. In recent years, the study of knowledge distillation has been of particular importance tolarge language models (LLMs). For LLMs, KD has emerged as an effective means of transferring advanced capabili...
LTDLow Threshold Detection LTDLaser Target Designator LTDLove to Death LTDLow Temperature Differential(Stirling engine) LTDLocal Telecommunications Division(Sprint) LTDLetter to Doctor LTDLocal Telephone Division LTDLight Toned Deposit(planetary science) ...
Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differ
For an image classification problem, scenarios like blurry, out-of-focus, distorted, as well as irrelevant/outlier images will disrupt the model training process and affect the performance. By curating your data, you'll ensure better performance and accuracy, and achieve more optimal, relevant, ...
Overall, CNNs are a powerful and effective deep learning architecture for processing visual data. They have significantly advanced the state of the art in computer vision and image understanding, enabling applications such as facial recognition, object detection, and self-driving cars. With ongoing re...
+(-)D indicates with (out) DatasetCache Most general-purpose databases take too much time to load data. After looking into the underlying implementation, we find that data go through too many layers of interfaces and unnecessary format transformations in general-purpose database solutions. Such ov...
"On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective".Yu-An Liu et al.arXiv 2023. [Paper] IncDSI:"IncDSI: Incrementally Updatable Document Retrieval".Varsha Kishore et al.ICML 2023. [Paper] CLEVER:"Continual Learning for Generative Retrieval over Dynamic Corpora...