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Probabilistes Reference
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26 documents available in our comprehensive collection of Probabilistes Reference resources. Find practical guides, tutorials, and documentation to enhance your knowledge.
Machine Learning (L11.1-prob-models.pdf)
1002 KBEN 45 pages
Machine learning and data mining involve probabilistic modeling to handle uncertain inferences from data. Probability theory is used to model uncertainty, enabling inference and prediction through probabilities. Applications include machine learning, computer vision, and NLP.
Slides (baydin-2019-neurips-slides.pdf)
7.65 MBEN 67 pages
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, involving probabilistic programming, deep learning, and neural networks,...
Stochastic Planning Inference (wu22a.pdf)
548 KBEN 12 pages
Stochastic planning is reduced to probabilistic inference in large discrete graphical models, requiring approximation schemes due to hardness of inference.
Deprojection Recovery (1909.00475.pdf)
2.07 MBEN 10 pages
We introduce visual deprojection, recovering an image or video collapsed along a dimension, and propose a probabilistic model and variational inference...
Endometrial Adenocarcinoma Prognosis and Survival Analysis (sdrtodxfsokkiaconverter.pdf)
184 KBEN 2 pages
The text describes a software converter ("Sdrtodxfsokkiaconverter") and includes a reference to a medical study on endometrial adenocarcinoma survival rates and relapse probabilities based on different treatment approaches
RTE Proceedings (D15-1185.pdf)
304 KBEN 6 pages
Recognizing Textual Entailment Using Probabilistic Inference:
The authors propose a method to recognize textual entailment (RTE) using predicate-argument...
Loss as Model Inconsistency (richardson22b.pdf)
717 KBEN 30 pages
Richardson argues that loss function choice in probabilistic dependency graphs (PDGs) should align with the model, not personal preference
RStan Package (rstan.pdf)
330 KBEN 82 pages
R package 'rstan' provides interface to Stan, a probabilistic programming language. It enables Bayesian statistical inference via Markov Chain Monte Carlo and other methods. Version 2.32.7 is available.
UTexas: Probabilistic Hypothesis Generation for TAC SM-KBP Task 3 (TAC2018.UTexas.proceedings.pdf)
106 KBEN 5 pages
Generates coherent hypotheses probabilistically.
PDF (Machine Learning_ A Probabilistic Perspective Murphy 2012-08-24.pdf)
25.69 MBEN 1098 pages
A Probabilistic Perspective by Kevin P.
Forecasting IBOVESPA Index with Fuzzy Logic (Newton-e-Outros.pdf)
221 KBEN 17 pages
This research applies fuzzy logic to predict the direction of price changes for the São Paulo Stock Exchange Index (IBOVESPA), utilizing 2,000 daily data points from January onwards. It offers a novel method for stock market forecasting.
Vorontsov, Konstantin, and Anna Potapenko. 2014. "Tutorial on Probabilistic Topic Modeling: Additive Regularization for Stochast (Voron14aist.pdf)
460 KBEN 18 pages
Konstantin Vorontsov and Anna Potapenko present a tutorial on probabilistic topic modeling, introducing a novel non-Bayesian approach called Additive...
Presentation Slides (Slides-Johan-Ugander.pdf)
13.58 MBEN 40 pages
Johan Ugander discusses learning preferences with irrelevant alternatives, focusing on choice systems as mathematical objects, and explores discrete choice,
https://files.emailmeform.com/2071943/GbrsaMWo/16.pdf (16.pdf)
43 KBEN 1 page
one proposes a probabilistic model for machine code learning, allowing for learning code that cannot be learned by traditional models, and the other presents a...
pdf (2020.findings-emnlp.70.pdf)
1.18 MBEN 10 pages
Neural dialogue response generation has gained popularity, but models trained with Maximum Likelihood Estimation (MLE) objective function suffer from...
Technical Report (Kappes2015a.pdf)
1.1 MBEN 12 pages
Researchers propose a probabilistic correlation clustering approach using perturbed multicuts, enabling the representation of uncertainty in image partitions...
Probabilistic Multimodal Modeling for Human-Robot Interaction Tasks (p47.pdf)
4.51 MBEN 9 pages
Probabilistic Multimodal Modeling for Human-Robot Interaction Tasks: This work introduces a reformulation of Interaction Primitives, called ensemble Bayesian...
Machine Learning (L11.2-prob-models-em.pdf)
945 KBEN 20 pages
The content covers machine learning and data mining, including unsupervised and supervised learning, probabilistic modeling, and expectation maximization.
Macroeconomic Forecasts: NBP Survey Results (Sep 2023) (Opis-wynikow-rundy-Ankiety-Makroekonomicznej-NBP-z-wrzesnia-2023-r.pdf)
623 KBPT 18 pages
Prognozy makroekonomiczne profesjonalnych prognostów. Wyniki Ankiety Makroekonomicznej NBP, Runda: wrzesień 2023 r. Synteza: prognozy probabilistyczne dla inflacji CPI, tempo wzrostu PKB i stopy referencyjnej NBP w latach 2023-2025.
Course Syllabus (syllabusss23.pdf)
27 KBEN 2 pages
Theory and Practice II" covers the probabilistic and statistical foundations of forecasting, with a focus on maximizing the sharpness of predictive...
etherpad text (IVOA_DAL_RM13.pdf)
45 KBEN 4 pages
The IVOA DAL WG Running Meeting #13 discussed the status of LineTAP, a TAP view based on VAMDC focused on common use cases.
![Preview of [PDF]](/images/pdf/64/85/43/64854388-01d9-4e5e-9367-e01cf8f198dd.png)
[PDF] (pronobis2017icml-padl.pdf)
1.04 MBEN 9 pages
LibSPN is a Python library for learning and inference with Sum-Product Networks (SPNs) and TensorFlow, aiming to become a platform for the machine learning...
electronic edition @ stanford.edu (open access) (intro-innovative.pdf)
553 KBEN 3 pages
The increasing use of Whole Genome Sequencing (WGS) and Whole Exome Sequencing (WES) in clinical settings has made it difficult to determine the causal variant...
Hawkes Edge Model (201_main_paper.pdf)
684 KBEN 10 pages
The Hawkes Edge Partition Model analyzes continuous-time event-based temporal networks. It infers community structure and interaction dynamics among entities using mutually-exciting Hawkes processes. The model modulates interaction dynamics based on latent representations.
![Preview of arXiv:0907.4010v1 [stat.CO] 23 Jul 2009](/images/pdf/63/3e/51/633e5171-231b-40d0-9e0b-48f760c72ff1.png)
arXiv:0907.4010v1 [stat.CO] 23 Jul 2009 (0907.4010v1.pdf)
101 KBEN 10 pages
It addresses challenges in Bayesian inference for models with censored or order-restricted parameters, where analytical computations are difficult. The methods utilize accept-reject sampling, Gibbs sampling, and Markov Chain Monte-Carlo techniques.
Pragmatic Reasoning (2005.06641.pdf)
1.04 MBEN 12 pages
Human pragmatic reasoning is viewed through the Rate-Distortion framework. The Rational Speech Act (RSA) framework formulates pragmatic reasoning as probabilistic speakers and listeners reasoning about each other. RSA recursion optimizes a tradeoff between expected utility and...
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