这次介绍的是Qi Pang等人发表在NDSS'24上的论文MPCDIFF,论文链接如下: https://www.ndss-symposium.org/ndss-paper/mpcdiff-testing-and-repairing-mpc-hardened-deep-learning-models/开源代码如下: https…
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c
DiffPackis a novel torsional diffusion model designed for predicting the conformation of protein side-chains based on their backbones, as introduced inarxiv link. By learning the joint distribution of side-chain torsional angles through a process of diffusing and denoising on the torsional space, ...
SameDiff另一个比较重要的功能是直接支持Tensorflow模型的导入。在Deeplearning4j之前的版本中,直接支持的是导入Keras的模型,而导入TF的模型都需要间接通过Keras,因此并不方便。SameDiff支持导入大部分的TF算子,具体可以参考官方的测试demo工程(https:///deeplearning4j/TFOpTests)。这篇文章暂且先不详细介绍SameDiff支持...
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection Abstract 本文提出了一种在不利照明条件下检测行人的新方法。 我们的方法依赖于一种新型的跨模态学习框架,它基于两个主要阶段。 首先,给出一个多模态数据集,采用深度卷积网络学习非线性映射,对RGB和热图之间的关系进行建模。 然后,所学习的...
Understanding the structural basis for protein function and dysfunction can also accelerate the development of drugs and other therapeutics. Identifying the structural features that determine the biochemical differences between protein variants is often a difficult challenge, requiring one to consider the ...
xAI公司宣布将Grok的系统提示词(System Prompt)全部公开发布在GitHub上,这一决定源于一个事件:Grok在X平台上的自动回复机器人的系统提示词被人篡改,导致机器人对某个敏感话题做出了违反平台规则的回复。 系统提示词仓库地址:https://github.com/xai-org/grok-prompts/tree/main其中包括对话,deepres… ...
Here we present DiffNets, self-supervised autoencoders that avoid such assumptions, and automatically identify the relevant features, by requiring that the low-dimensional representations they learn are sufficient to predict the biochemical differences between protein variants. For example, DiffNets ...
Deeplearning4J在Scala中的SameDiff：INDArrays到DataSetIterator作为www.example.com的输入sameDiff.fit你...
Efficient and Scalable Physics-Informed Deep Learning Collocation-based PINN PDE solvers for prediction and discovery methods on top ofTensorflow2.X for multi-worker distributed computing. Use TensorDiffEq if you require: A meshless PINN solver that can distribute over multiple workers (GPUs) for for...