Literatura académica sobre el tema "Path signatures"
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Artículos de revistas sobre el tema "Path signatures"
Kalsi, Jasdeep, Terry Lyons y Imanol Perez Arribas. "Optimal Execution with Rough Path Signatures". SIAM Journal on Financial Mathematics 11, n.º 2 (enero de 2020): 470–93. http://dx.doi.org/10.1137/19m1259778.
Texto completoCartea, Álvaro, Imanol Pérez Arribas y Leandro Sánchez-Betancourt. "Double-Execution Strategies Using Path Signatures". SIAM Journal on Financial Mathematics 13, n.º 4 (21 de noviembre de 2022): 1379–417. http://dx.doi.org/10.1137/21m1456467.
Texto completoBoland, Philip J. "Signatures of indirect majority systems". Journal of Applied Probability 38, n.º 2 (junio de 2001): 597–603. http://dx.doi.org/10.1239/jap/996986765.
Texto completoBoland, Philip J. "Signatures of indirect majority systems". Journal of Applied Probability 38, n.º 02 (junio de 2001): 597–603. http://dx.doi.org/10.1017/s0021900200020064.
Texto completoFang, Yuan, Zhe Su, Jing Xie, Ruidong Xue, Qi Ma, Yanmeng Li, Yifan Zhao et al. "Genomic signatures of pancreatic adenosquamous carcinoma (PASC)". Journal of Pathology 243, n.º 2 (5 de septiembre de 2017): 155–59. http://dx.doi.org/10.1002/path.4943.
Texto completoJiang, Yunjiang y Weijun Xu. "On the Number of Turns in Reduced Random Lattice Paths". Journal of Applied Probability 50, n.º 2 (junio de 2013): 499–515. http://dx.doi.org/10.1239/jap/1371648957.
Texto completoJiang, Yunjiang y Weijun Xu. "On the Number of Turns in Reduced Random Lattice Paths". Journal of Applied Probability 50, n.º 02 (junio de 2013): 499–515. http://dx.doi.org/10.1017/s0021900200013528.
Texto completoShestakova, Tatyana. "On A. D. Sakharov’s Hypothesis of Cosmological Transitions with Changes in the Signature of the Metric". Universe 7, n.º 5 (17 de mayo de 2021): 151. http://dx.doi.org/10.3390/universe7050151.
Texto completoWebster, Jonathan A., Andrew H. Beck, Mimansa Sharma, Inigo Espinosa, Britta Weigelt, Marthe Schreuder, Kelli D. Montgomery, Kristin C. Jensen, Matt van de Rijn y Robert West. "Variations in stromal signatures in breast and colorectal cancer metastases". Journal of Pathology 222, n.º 2 (21 de mayo de 2010): 158–65. http://dx.doi.org/10.1002/path.2738.
Texto completoKumar, Pankaj, Saurabh Kumar Sharma y Kaveri Umesh Kadam. "Prolong the lifetime of sensor monitoring system using schedule matrix while employing digital signatures". Journal of Information and Optimization Sciences 44, n.º 7 (2023): 1327–46. http://dx.doi.org/10.47974/jios-1286.
Texto completoTesis sobre el tema "Path signatures"
Chevyrev, Ilya. "Characteristic functions of path signatures and applications". Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:3dd5e063-bde0-434f-a781-61d3fe22aaa1.
Texto completoBoedihardjo, Horatio S. "Signatures of Gaussian processes and SLE curves". Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:5f835640-d3f5-4b03-b600-10d897644ced.
Texto completoInzirillo, Hugo. "Contributions to Econometric and Deep Learning Methods for Time Series Forecasting". Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAG005.
Texto completoThis thesis, structured in four distinct parts, contributes to enriching the fields of deep learning and nonlinear econometrics. Traditional models have often shown weaknesses in capturing the nonlinear behaviors and regime shifts characteristic of digital assets. This thesis focuses on improving the prediction of returns and volatility of this new asset class through the development of new neural network architectures and innovative methodologies. In a first part, we introduce Temporal Kolmogorov-Arnold Networks (TKANs) as well as a new transformer-based architecture (TKAT) based on TKANs for time series forecasting. These models integrate memory management and attention mechanism to capture the complex dynamics of financial markets. Our results show that TKAN and TKAT outperform traditional recurrent models (LSTM, GRU) in terms of stability and prediction accuracy, particularly over longer time horizons. The second part proposes a new approach for modeling market regimes using recurrent neural networks and new Markov-Switching GARCH dynamics. This former approach allows to detect market regimes and estimate transition probabilities between different states. The results show a significant improvement in the detection and prediction of market regimes compared to traditional models.The latter models define new meaningful MS-GARCH specifications and convenient simulation-based estimations procedures.In the third part, we explore the use of signatures for portfolio construction. A signature-based classification method is developed to select the most representative assets of each cluster, thus improving the risk-return ratio. Portfolios built with this methodology show superior performances compared to standard portfolios. The last part of this thesis addresses volatility modeling and anomaly detection. We propose a new LSTM layer, the Attention Free Long Short-Term Memory (AF-LSTM), for volatility prediction. This new layer shows superior predictive performances compared to the original version. For anomaly detection, a conditional autoencoder (AF-CAE) is introduced, providing better anomaly detection, reducing false positives. This thesis proposes several contributions in the field of time series prediction; the results demonstrate improvements in terms of accuracy and robustness, opening new perspectives for the modeling and management of financial assets
Xu, Weijun. "Inverting the signature of a path". Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:954ff1e3-9162-456a-91a3-39734854cde2.
Texto completoGeng, Xi. "The signature of a rough path : uniqueness". Thesis, University of Oxford, 2015. http://ora.ox.ac.uk/objects/uuid:f15c0439-2b30-4738-9eab-0dffd86bed69.
Texto completoNi, Hao. "The expected signature of a stochastic process". Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:e0b9e045-4c09-4cb7-ace9-46c4984f16f6.
Texto completoJanssen, Arend. "Order book models, signatures and numerical approximations of rough differential equations". Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:264e96b3-f449-401b-8768-337acab59cab.
Texto completoHabermann, Karen. "Geometry of sub-Riemannian diffusion processes". Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/271855.
Texto completoFaye, Mbaye. "Signature infrarouge et modélisation pour la télédétection de deux gaz : SF6 et RuO4". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS182.
Texto completoThis work is a contribution to the spectroscopic study of two gases of anthropogenic origin for which the modeling of the infrared signature may allow a quantification in releases in the atmosphere. Sulfur hexafluoride (SF₆) is mainly rejected by the electrical industry, which uses it as a gaseous insulator and its concentration increases rapidly in the atmosphere (of the order of 7 per cent per year). It is a potent greenhouse gas listed in the Kyoto Protocol because its intense absorption around 10 μm issituated in a window of atmospheric transparency and its lifetime in the upper atmosphere (approximately 3200 years) confers an exceptionally high radiative transfer coefficient (Global WarmingPotential, or GWP equal to 23900 times that of carbon dioxide,CO2). The detection and quantification of this gas by its infrared signature via satellite measurements requires a very accurate modeling of the absorption spectra, incompletely known. For SF₆,in particular because of the fact that this heavy molecule presents a large number of vibrational levels of low energy, there exist hotbands in the region of atmospheric absorption around its most intense fundamental absorption (v₃); these involve excited states little or not characterized. Thus, at ambient temperature, only 32% of the molecules are located in the vibrational ground state. Current databases contain only data for the fundamental vibrationband. To compensate for this lack, it is therefore necessary toobserve a number of transitions from the ground state to the excited levels of low energy used corresponding to initial states of the hot bands and to acquire data for modeling also levels with two quanta of vibration constituting the upper levels of arrival of thes ehot bands.This work is a contribution to the spectroscopic study of two gases of anthropogenic origin for which the modeling of the infrared signature may allow a quantification in releases in the atmosphere.Sulfur hexafluoride (SF₆) is mainly rejected by the electricalindustry, which uses it as a gaseous insulator and its concentration increases rapidly in the atmosphere (of the order of 7 per cent peryear). It is a potent greenhouse gas listed in the Kyoto Protocolbecause its intense absorption around 10 μm is situated in awindow of atmospheric transparency and its lifetime in the upper atmosphere (approximately 3200 years) confers an exceptionally high radiative transfer coefficient (Global Warming Potential, orGWP equal to 23900 times that of carbon dioxide, CO2). The detection and quantification of this gas by its infrared signature via satellite measurements requires a very accurate modeling of theabsorption spectra, incompletely known. For SF6, in particular because of the fact that this heavy molecule presents a largenumber of vibrational levels of low energy, there exist hot bands in the region of atmospheric absorption around its most intensefundamental absorption (v3); these involve excited states little or not characterized. Thus, at ambient temperature, only 32 % of themolecules are located in the vibrational ground state. Current databases contain only data for the fundamental vibration band. Tocompensate for this lack, it is therefore necessary to observe a number of transitions from the ground state to the excited levels oflow energy used corresponding to initial states of the hot bands andto acquire data for modeling also levels with two quanta ofvibration constituting the upper levels of arrival of these hot bands
Kebichi, Omar. "Techniques et outils de CAO pour la génération automatique de test intégré pour RAMs". Grenoble INPG, 1994. http://www.theses.fr/1994INPG0062.
Texto completoLibros sobre el tema "Path signatures"
Chien-ming, Chin, University of Illinois at Urbana-Champaign. Electromagnetic Communication Laboratory. y United States. National Aeronautics and Space Administration., eds. Electromagnetic scattering from realistic targets: Final report for NASA NAG 3-1474. Urbana, IL: Electromagnetics Laboratory, Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1997.
Buscar texto completoBellman, Geoffrey M. Your Signature Path: Gaining New Perspectives on Life and Work. Berrett-Koehler Publishers, Incorporated, 1996.
Buscar texto completoYour signature path: Gaining new perspectives on life and work. San Francisco: Berrett-Koehler Publishers, 1996.
Buscar texto completoDiscovering your soul signature: A 33-day path to purpose, passion, & joy. 2014.
Buscar texto completoMatrix, The: Path of Neo(tm) Official Strategy Guide (Bradygames Signature Series Guide). BRADY GAMES, 2005.
Buscar texto completoLatour, Melinda. Santana and the Metaphysics of Tone. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199985227.003.0010.
Texto completoKitses, Jim. Horizons West. Bloomsbury Publishing Plc, 2007. http://dx.doi.org/10.5040/9781838711276.
Texto completoLiechty, Edward A. y Martin M. Fisher, eds. Coding for Pediatrics, 2016. 21a ed. American Academy of Pediatrics, 2015. http://dx.doi.org/10.1542/9781581109597.
Texto completoLiechty, Edward A., Cindy Hughes y Becky Dolan, eds. Coding for Pediatrics, 2014. American Academy of Pediatrics, 2013. http://dx.doi.org/10.1542/9781581108354.
Texto completoCapítulos de libros sobre el tema "Path signatures"
Wang, Chenyang, Ling Luo y Uwe Aickelin. "Quasi-Periodicity Detection via Repetition Invariance of Path Signatures". En Advances in Knowledge Discovery and Data Mining, 301–13. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33383-5_24.
Texto completoNeginhal, Mradula, Khaled Harfoush y Harry Perros. "Measuring Bandwidth Signatures of Network Paths". En NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet, 1072–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72606-7_92.
Texto completoHuang, Zi, Xiaofang Zhou, Heng Tao Shen y Dawei Song. "3D Protein Structure Matching by Patch Signatures". En Lecture Notes in Computer Science, 528–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11827405_52.
Texto completoOliveira, Dario Augusto Borges y Matheus Palhares Viana. "Using 1D Patch-Based Signatures for Efficient Cascaded Classification of Lung Nodules". En Patch-Based Techniques in Medical Imaging, 67–75. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00500-9_8.
Texto completoFermanian, Adeline, Jiawei Chang, Terry Lyons y Gérard Biau. "The Insertion Method to Invert the Signature of a Path". En Recent Advances in Econometrics and Statistics, 575–95. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61853-6_29.
Texto completoSong, Sung Keun, Hee Yong Youn y Kang Shin Lee. "A New Digital Signature and Certificate Architecture with Shortest Certification Path". En Lecture Notes in Computer Science, 1–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24693-0_1.
Texto completoLy Van, B., S. Garcia-Salicetti y B. Dorizzi. "Fusion of HMM’s Likelihood and Viterbi Path for On-line Signature Verification". En Biometric Authentication, 318–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_29.
Texto completoZhang, Xin, Jiale Cheng, Hao Ni, Chenyang Li, Xiangmin Xu, Zhengwang Wu, Li Wang, Weili Lin, Dinggang Shen y Gang Li. "Infant Cognitive Scores Prediction with Multi-stream Attention-Based Temporal Path Signature Features". En Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 134–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59728-3_14.
Texto completoShin, Hakgene, Heeju Lee y Jaewoo Chang. "A Concatenated Signature Scheme on Path Dictionary for Query Processing of Composite Objects". En OOIS’97, 44–54. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1525-0_5.
Texto completoIgnatidis, Panagiotis, Henrik von der Haar, Christoph Hennecke y Friedrich Dinkelacker. "Impact of Mixing on the Signature of Combustor Defects". En Regeneration of Complex Capital Goods, 95–113. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-51395-4_6.
Texto completoActas de conferencias sobre el tema "Path signatures"
Oppeneer, Martien, Piet Bijl, Judith Dijk, Miranda van Iersel y Johan-Martijn ten Hove. "Target acquisition modeling over the exact optical path: extending the EOSTAR TDA with the TOD sensor performance model". En Target and Background Signatures, editado por Karin U. Stein y Ric Schleijpen. SPIE, 2017. http://dx.doi.org/10.1117/12.2278848.
Texto completoMorley, Sam y Terry Lyons. "RoughPy". En Python in Science Conference. SciPy, 2024. http://dx.doi.org/10.25080/dxwy3560.
Texto completoMoore, Paul, Theodor-Mihai Iliant, Filip-Alexandru Ion, Yue Wu y Terry Lyons. "Path Signatures for Non-Intrusive Load Monitoring". En ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747285.
Texto completoZhang, Ze, Sunghyun Park y Scott Mahlke. "Path Sensitive Signatures for Control Flow Error Detection". En LCTES '20: 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3372799.3394360.
Texto completoWilson, David J., R. Burt Dedmon, W. W. Montgomery y C. E. Craven. "Doppler Signatures of Hard Targets". En Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/clr.1987.tha4.
Texto completoLoch, Adrian, David Meier y Matthias Hollick. "How did you get here? PHY-layer path signatures". En 2014 IEEE 15th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM). IEEE, 2014. http://dx.doi.org/10.1109/wowmom.2014.6919019.
Texto completoFlanigan, Edward, Arkan Abdulrahman y Spyros Tragoudas. "Sequential Path Delay Fault Identification Using Encoded Delay Propagation Signatures". En 2008 9th International Symposium of Quality of Electronic Design (ISQED). IEEE, 2008. http://dx.doi.org/10.1109/isqed.2008.4479811.
Texto completoChen, Yangjun, Yong Shi y Yibin Chen. "Tree inclusion algorithm, signatures and evaluation of path-oriented queries". En the 2006 ACM symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1141277.1141521.
Texto completoHaderlein, Jonas F., Andre D. H. Peterson, Parvin Zarei Eskikand, Mark J. Cook, Anthony N. Burkitt, David B. Grayden y Iven M. Y. Mareels. "Revisiting Seizure Prediction with Path Signatures: the Limitations of System Identification". En 2024 Australian & New Zealand Control Conference (ANZCC). IEEE, 2024. http://dx.doi.org/10.1109/anzcc59813.2024.10432829.
Texto completoVarma, Nakul, Sujit Jadhav, Kumar Manish, Ravi Chandak, Avdesh Negi, Ajay Jha y Avinash Bohra. "Horizontal Sucker Rod Pumping Wells – Novel Unconventional Dyna Card Signatures Interpretation for Pump & Rod Run-life Optimisation". En Asia Pacific Unconventional Resources Symposium. SPE, 2023. http://dx.doi.org/10.2118/217279-ms.
Texto completoInformes sobre el tema "Path signatures"
Simandl, G. J., R. J. D'Souza, S. Paradis y J. Spence. Rare-earth element content of carbonate minerals in sediment-hosted Pb-Zn deposits, southern Canadian Rocky Mountains. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/328001.
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