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Related papers: When Outliers Are Different

200 papers

Gamma ray burst (GRB) objects are now widely thought to be at cosmological distances, and thus represent enormous energy emission. Gamma ray spectra extending to $GeV$ energies suggest the possiblity of accompanying neutrino emission, and…

High Energy Physics - Phenomenology · Physics 2007-05-23 T. J. Weiler , W. A. Simmons , S. Pakvasa , J. G. Learned

Fast radio bursts (FRBs) are enigmatic high-energy events with unknown origins, which are observationally divided into two categories, i.e., repeaters and non-repeaters. However, there are potentially a number of non-repeaters that may be…

High Energy Astrophysical Phenomena · Physics 2025-02-14 Wan-Peng Sun , Ji-Guo Zhang , Yichao Li , Wan-Ting Hou , Fu-Wen Zhang , Jing-Fei Zhang , Xin Zhang

We present different methods of unsupervised learning which can be used for outlier detection in high energy nuclear collisions. The UrQMD model is used to generate the bulk background of events as well as different variants of outlier…

High Energy Physics - Experiment · Physics 2021-05-26 Punnathat Thaprasop , Kai Zhou , Jan Steinheimer , Christoph Herold

The energy and waiting time distributions are important properties for understanding the physical mechanism of repeating fast radio bursts (FRBs). Recently, the Five-hundred-meter Aperture Spherical radio Telescope (FAST) detected the…

High Energy Astrophysical Phenomena · Physics 2021-10-20 G. Q. Zhang , P. Wang , Q. Wu , F. Y. Wang , D. Li , Z. G. Dai , B. Zhang

If gamma ray bursts are highly collimated, the energy requirements of each event may be reduced by several (~ 4-6) orders of magnitude, and the event rate increased correspondingly. Extreme conditions in gamma ray bursters lead to highly…

Astrophysics · Physics 2009-10-30 James E. Rhoads

With the rise of machine learning and deep learning based applications in practice, monitoring, i.e. verifying that these operate within specification, has become an important practical problem. An important aspect of this monitoring is to…

Machine Learning · Computer Science 2021-06-29 Thomas Viehmann

Fast radio bursts (FRBs) are millisecond-duration extragalactic transients, observationally classified as repeaters or nonrepeaters. This classification may be biased, as some apparently non-repeating sources could simply have undetected…

High Energy Astrophysical Phenomena · Physics 2025-12-09 N. Mankatwit , P. Thongkonsing , S. Loekkesee , P. Chainakun , W. Luangtip , S. Sanpa-arsa

Outlier detection can serve as an extremely important tool for researchers from a wide range of fields. From the sectors of banking and marketing to the social sciences and healthcare sectors, outlier detection techniques are very useful…

Methodology · Statistics 2023-12-12 Efthymios Costa , Ioanna Papatsouma

Often the challenge associated with tasks like fraud and spam detection is the lack of all likely patterns needed to train suitable supervised learning models. This problem accentuates when the fraudulent patterns are not only scarce, they…

Machine Learning · Computer Science 2019-05-08 Utkarsh Porwal , Smruthi Mukund

Outflows are common in many astrophysical systems which contain black holes and neutron stars. Difference between stellar outflows and outflows from these systems is that the outflows in these systems have to form out of the inflowing…

Astrophysics · Physics 2007-05-23 Sandip K. Chakrabarti

Normalizing flows are prominent deep generative models that provide tractable probability distributions and efficient density estimation. However, they are well known to fail while detecting Out-of-Distribution (OOD) inputs as they directly…

Machine Learning · Computer Science 2021-11-17 Nishant Kumar , Pia Hanfeld , Michael Hecht , Michael Bussmann , Stefan Gumhold , Nico Hoffmann

The discovery of the `Lorimer Burst', a little over a decade ago, ignited renewed interest in searching for short-duration radio transients. This event is now considered to be the first established Fast Radio Burst (FRB), which is a class…

High Energy Astrophysical Phenomena · Physics 2018-04-18 J. W. T. Hessels

Observationally, fast radio bursts (FRBs) can be divided into repeating and apparently non-repeating (one-off) ones. It is unclear whether all FRBs repeat and whether there are genuine non-repeating FRBs. We attempt to address these…

High Energy Astrophysical Phenomena · Physics 2021-01-13 Shunke Ai , He Gao , Bing Zhang

We have performed searches for isolated flares and for steady flickering in Gamma Ray Burst light curves on the microsecond to millisecond time scales. Two bursts out of our sample of 20 revealed four isolated flares with time scales from…

Astrophysics · Physics 2009-09-25 Katharine C. Walker , Bradley E. Schaefer , E. E. Fenimore

Gamma-ray bursts (GRBs) are the most powerful explosions in the universe and probe physics under extreme conditions. GRBs divide into two classes, of short and long duration, thought to originate from different types of progenitor systems.…

High Energy Astrophysical Phenomena · Physics 2014-11-20 LAT Collaboration

Randomly oriented relativistic emitters in a relativistically expanding shell provides an alternative to internal shocks as a mechanism for producing GRBs' variable light curves with efficient conversion of energy to radiation. In this…

High Energy Astrophysical Phenomena · Physics 2015-05-13 Ayah Lazar , Ehud Nakar , Tsvi Piran

We present a novel notion of outlier, called the Concentration Free Outlier Factor, or CFOF. As a main contribution, we formalize the notion of concentration of outlier scores and theoretically prove that CFOF does not concentrate in the…

Machine Learning · Computer Science 2019-09-18 Fabrizio Angiulli

Gamma-ray bursts are believed to be some catastrophic event in which material is ejected at a relativistic velocity, and internal collisions within this ejecta produce the observed $\gamma$-ray flash. The angular size of a causally…

Astrophysics · Physics 2009-10-31 Pawan Kumar , Tsvi Piran

Patterns that appear rarely or unusually in the data can be defined as outlier patterns. The basic idea behind detecting outlier patterns is comparison of their relative frequencies with frequent patterns. Their frequencies of appearance…

Databases · Computer Science 2015-07-08 Archana N. , S. S. Pawar

Assuming an exponential power distribution is one way to deal with outliers in regression and clustering, which can increase the robustness of the analysis. Gaussian distribution is a special case of an exponential distribution. And an…

Methodology · Statistics 2020-12-22 Xiao Chen
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