A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios
arXiv:2512.23748v1 Announce Type: new
Abstract: For complex simulation problems, inferring parameters of scientific interest often precludes the use of classical likelihood-based techniques due to intractable likelihood functions. Simulation-based inference (SBI) methods forego the need for explici...
Large Language Models for EDA Cloud Job Resource and Lifetime Prediction
arXiv:2512.19701v1 Announce Type: new
Abstract: The rapid growth of cloud computing in the Electronic Design Automation (EDA) industry has created a critical need for resource and job lifetime prediction to achieve optimal scheduling. Traditional machine learning methods often struggle with the com...
Convolutional-neural-operator-based transfer learning for solving PDEs
arXiv:2512.17969v1 Announce Type: new
Abstract: Convolutional neural operator is a CNN-based architecture recently proposed to enforce structure-preserving continuous-discrete equivalence and enable the genuine, alias-free learning of solution operators of PDEs. This neural operator was demonstrate...
Latent Action World Models for Control with Unlabeled Trajectories
arXiv:2512.10016v1 Announce Type: new
Abstract: Inspired by how humans combine direct interaction with action-free experience (e.g., videos), we study world models that learn from heterogeneous data. Standard world models typically rely on action-conditioned trajectories, which limits effectiveness...
Cluster-Dags as Powerful Background Knowledge For Causal Discovery
arXiv:2512.10032v1 Announce Type: new
Abstract: Finding cause-effect relationships is of key importance in science. Causal discovery aims to recover a graph from data that succinctly describes these cause-effect relationships. However, current methods face several challenges, especially when dealin...
Beyond DeepSeek: An Overview of Chinese AI Tigers and Their Cutting-Edge Innovations
The recent disruption caused by DeepSeek’s R1 model sent shockwaves through the AI community, demonstrating that Chinese AI advancements may have been underestimated. The model’s performance, rivaling some of the most advanced offerings from OpenAI and Anthropic at a fraction of the cost, signaled a...
An overview of classifier-free diffusion guidance: impaired model guidance with a bad version of itself (part 2)
How to apply classifier-free guidance (CFG) on your diffusion models without conditioning dropout? What are the newest alternatives to generative sampling with diffusion models? Find out in this article!
Limited Time Offer: Get Your Exclusive Online Passes to the Chatbot Conference — Act Fast!
🚀 Limited Time Offer: Get Your Exclusive Online Passes to the Chatbot Conference — Act Fast! 🚀Exciting news ahead! With an incredible surge of enthusiasm, we're rolling out an exclusive Online Only option for this year's Chatbot Conference, kicking things off with an absolutely phenomenal launch!Tod...
An overview of classifier-free guidance for diffusion models
Learn more about the nuances of classifier-free guidance, the core sampling mechanism of current state-of-the-art image generative models called diffusion models.