The Fortran 77 codes for the open-loop and the closed-loop simulations for the Tennessee Eastman process (TEP) as well as the training and testing data files used for evaluating the data-driven methods (PCA, PLS, FDA, and CVA).

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully accelerates simulations by up to 2 billion times in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

Analyses of single-cell recordings from mouse ventral tegmental area are consistent with a model of reinforcement learning in which the brain represents possible future rewards not as a single mean of stochastic outcomes, as in the canonical model, but instead as a probability distribution.

Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems.

In one of the breakthrough experiments, researchers at the University of Bristol’s Quantum Engineering Technology Labs (QET Labs) demonstrate the quantum teleportation of information between two programmable chip for the first time, which they remark is a cornerstone of quantum communications and quantum computing.

Quantum teleportation offers quantum state transfer of a quantum particle from one place to another by utilising entanglement. Teleportation is not only useful for quantum communication but is a fundamental building-block of optical quantum computing. Establishing an entangled communication link between two chips in the lab however has proven to be highly challenging.

“Each chip was then fully programmed to perform a range of demonstrations which utilise the entanglement.

“The flagship demonstration was a two-chip teleportation experiment, whereby the individual quantum state of a particle is transmitted across the two chips after a quantum measurement is performed. This measurement utilises the strange behaviour of quantum physics, which simultaneously collapses the entanglement link and transfers the particle state to another particle already on the receiver chip.”

Researchers at EPFL have developed an ultra-light robotic insect that uses its soft artificial muscles to move at 3 cm per second across different types of terrain. It can be folded or crushed and yet continue to move.

This year I sent out quite a few proposals to the majority of mobile conferences in Europe. Some ignored me, the others replied with automated rejections. However, some accepted and it was fun. Here is what I've learned on the way.

A guide to document clustering with Python

This post overviews the paper Confident Learning: Estimating Uncertainty in Dataset Labels authored by Curtis G. Northcutt, Lu Jiang, and Isaac L. Chuang.

SCION is the first clean-slate Internet architecture designed to provide route control, failure isolation, and explicit trust information for end-to-end communication. SCION organizes existing ASes into groups of independent routing planes, called isolation domains, which interconnect to provide global connectivity. Isolation domains provide natural isolation of routing failures and misconfigurations, give endpoints strong control for both inbound and outbound traffic, provide meaningful and enforceable trust, and enable scalable routing updates with high path freshness. As a result, the SCION architecture provides strong resilience and security properties as an intrinsic consequence of its design. Besides high security, SCION also provides a scalable routing infrastructure, and high efficiency for packet forwarding. As a path-based architecture, SCION end hosts learn about available network path segments, and combine them into end-to-end paths that are carried in packet headers. Thanks to embedded cryptographic mechanisms, path construction is constrained to the route policies of ISPs and receivers, offering path choice to all the parties: senders, receivers, and ISPs. This approach enables path-aware communication, an emerging trend in networking. These features also enable multi-path communication, which is an important approach for high availability, rapid failover in case of network failures, increased end-to-end bandwidth, dynamic traffic optimization, and resilience to DDoS attacks.

During the writing phase of an academic paper, common tasks include downloading PDFs of publications and getting their references into your bibliography. However, I am not a fan of navigating the slow, bloated, tracker-filled, and distracting webpages of academic journals and publication aggregators. For some reason, many publishers decided that clicking the "Download PDF" link should redirect the user to an unusable in-browser PDF viewer instead of providing the PDF file directly. While the majority of journal webpages provide formatted citations for their publications, these are inconsistent in style and content.

Why conrad?

• Never miss CFP deadlines again. conrad remind can remind you every time you open a terminal!
• Query and explore events using tags, names, locations, and dates. conrad show --cfp will tell you about events where the CFP is open!
• Crawlers update events twice a week! (Monday and Thursday at 00:00 UTC)

The most successful people are not the most talented, just the luckiest, a new computer model of wealth creation confirms. Taking that into account can maximize return on many kinds of investment.

Topical keyphrase extraction is used to summarize large collections of text
documents. However, traditional methods cannot properly reflect the intrinsic
semantics and relationships of keyphrases because they rely on a simple
term-frequency-based process. Consequently, these methods are not effective in
obtaining significant contextual knowledge. To resolve this, we propose a
topical keyphrase extraction method based on a hierarchical semantic network
and multiple centrality network measures that together reflect the hierarchical
semantics of keyphrases. We conduct experiments on real data to examine the
practicality of the proposed method and to compare its performance with that of
existing topical keyphrase extraction methods. The results confirm that the
proposed method outperforms state-of-the-art topical keyphrase extraction
methods in terms of the representativeness of the selected keyphrases for each topic. The proposed method can effectively reflect intrinsic keyphrase semantics and interrelationships.

SchedViz is a tool for gathering and visualizing kernel scheduling traces on Linux machines. It helps to:

• quantify task starvation due to round-robin queueing,
• identify primary antagonists stealing work from critical threads,
• determine when core allocation choices yield unnecessary waiting,
• evaluate different scheduling policies,
• and much more.

Keyword extraction (also known as keyword detection or keyword analysis) is a text analysis technique that consists of automatically extracting the most important words and expressions in a text.

It helps summarize the content of a text and recognize the main topics which are being discussed.

The Dataverse Project - Dataverse.org

The Pulitzer prizewinner shares his advice for pleasing readers, editors and yourself.

Publishing a paper in academia is challenging, stimulating, and a bit baffling. Challenging because the research might fail. Stimulating because research may start assuming one outcome and finish with a totally different one. Baffling because after the paper is written and ready, I have to find it a home for