Probabilistic Circuits (PCs) are a promising avenue for probabilistic modeling. They combine advantages of probabilistic graphical models (PGMs) with those of neural networks (NNs). Crucially, however, they are tractable probabilistic models, supporting efficient and exact computation of many probabilistic inference queries, such as marginals and MAP. Further, since PCs are structured computation graphs, they can take advantage of deep-learning-style parameter updates, which greatly improves their scalability. However, this innovation also makes PCs prone to overfitting, which has been observed in many standard benchmarks. Despite the existence of abundant regularization techniques for both PGMs and NNs, they are not effective enough when applied to PCs.

As SARS-CoV-2 radiated across the planet in 2020, epidemiologists scrambled to predict its spread--and its deadly consequences. Often, they turned to models that not only simulate viral transmission and hospitalization rates, but can also predict the effect of interventions: masks, vaccines, or travel bans. But in addition to being computationally intensive, models in epidemiology and other disciplines can be black boxes: millions of lines of legacy code subject to finicky tunings by operators at research organizations scattered around the world. They don't always provide clear guidance. "The models that are used are often kind of brittle and nonexplainable," says Erica Briscoe, who was a program manager for the Automating Scientific Knowledge Extraction and Modeling (ASKEM) project at the Defense Advanced Research Projects Agency (DARPA).

We thank all reviewers for their valuable and constructive feedback. We will fix any typos, cite the reference (Durmus et al., 2016), clarify the Revs. We will add more clarification on the class of non-convex potentials at the beginning of the section. Rev. 1 - dimension dependence: Figure on the right shows the asymptotic bias vs To this end, we performed a wall time analysis, whose results were included in App. To summarize the findings, SRK-LD is 2.5-3 times The purpose was to demonstrate that (ii) has a smaller bias than (iii) .

Tesla sales have surged in the third quarter as buyers in the United States rushed to take advantage of electric vehicle (EV) tax credits that were eliminated under President Donald Trump's sweeping tax bill passed this year. On Thursday, the automaker reported a 7.4 percent increase in sales compared with the same period last year as demand was driven by customers looking to buy before the credits officially expired at the end of September. Tesla also delivered 481,166 units of its Model 3 compact sedan and Model Y crossover in the quarter, well above Wall Street expectations. The Elon Musk-led carmaker frequently talked up the expiry of the tax credits, using it alongside discounts and financing deals to spur sales and leases of its EVs. Investors are worried because sales are now expected to slump as the $7,500 federal tax credit disappears.

AMD's hardware teams have tried to redefine AI inferencing with powerful chips like the Ryzen AI Max and Threadripper. But in software, the company has been largely absent where PCs are concerned. That's changing, AMD executives say. AMD's Advancing AI event Thursday focused on enterprise-class GPUs like its Instinct lineup. But it's a software platform you may not have heard of, called ROCm, that AMD depends upon just as much.

A few days ago, Microsoft announced via the Windows Insider blog some new AI features and improvements for the Photos app. Among the new features is "Relight," which lets you adjust the lighting in a photo by placing up to three virtual light sources that can each be adjusted for color, intensity, and direction. There are also several built-in preset styles for quicker adjustments. With Relight, you can use the power of AI to dramatically change the mood, tone, and appearance of any photo. However, you'll need a Snapdragon-powered Copilot PC to take advantage of this feature right now.

When it comes to autonomous vehicles on city roads, that's been the approach in most of the world's countries. But on Tuesday, the UK announced it would put a cautious foot on the pedal, when the Department of Transport said it would accelerate plans to allow companies to operate self-driving cars on public roads in limited pilot programs starting spring of next year. The British government had initially planned to open up its roads for self-driving vehicles more than a year later, in the second half of 2027. "We can see what a massive economic opportunity this technology presents," Transport secretary Heidi Alexander tells WIRED in an interview. The department estimates the autonomous vehicle industry will create 38,000 jobs and generate 42 billion pounds ( 57 million US) for the country by 2035.

We would like to thank the reviewers for their thoughtful advice and feedback. Some reviewers were confused by the limitations of the approach. Some reviewers had questions about what pieces of Enzyme's implementation are novel from other AD systems. A reviewer asked about how experiments were prepared. Additional tests were created using Tapenade's web interface or replacing programs with Adepts A reviewer would have also liked to see Enzyme produce code for popular models.

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