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Questions tagged [monte-carlo]

36 questions
24
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1 answer

What is Monte Carlo dropout?

I understand how to use MC dropout from this answer, but I don't understand how MC dropout works, what its purpose is, and how it differs from normal dropout.
Arka Mallick
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1 answer

Estimating the value of $\pi$ with a Monte Carlo dartboard: $<$ or $\leq$?

I'm trying to figure out which is the proper way to estimate $\pi$ using the Monte Carlo method randomly distributing points in a square that also contains an inscribed circle. Some sources say to use the comparison of $\sqrt{x^2+y^2}\le 1$, while…
Oatmeal
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5
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2 answers

What is the intuition behind using Monte Carlo to solve a differential equation

Conceptually, I understand how a numerical method like Monte Carlo is used to solve a definite integral. Because integral of a function is the area bounded by the curve, the ratio of random points that land inside the curve to the total number of…
Victor
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4
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1 answer

What visualization I should choose for Monte Carlo simulations in timeline events?

I wasn't sure if I should open this question in Cross Validated or here. But since the question belongs to a bigger project related with Data Science, I chose this one. I will present a simplified version of my working project, since the original is…
Tasos
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3
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1 answer

Evaluating a trained Reinforcement Learning Agent?

I am new to reinforcement learning agent training. I have read about PPO algorithm and used stable baselines library to train an agent using PPO. So my question here is how do I evaluate a trained RL agent. Consider for a regression or…
chink
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2
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1 answer

Having a reward structure which gives high positive rewards compared to the negative rewards

I am training an RL agent using PPO algorithm for a control problem. The objective of the agent is to maintain temperature in a room. It is an episodic task with episode length of 9 hrs and step size(action being taken) for every 15 mins.During the…
chink
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2
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1 answer

MCMC for finding Bayesian Neural Network

Is someone familiar with such an approach: Suppose I want to build a bayesian neural network, with distributions over my parameters instead of point estimates. First I train my network with standard backprop. After training I start some MCMC…
Andreas Look
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2
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1 answer

Evaluating value functions in RL

I'm working my way through the book Reinforcement Learning by Richar S. Sutton and Andrew G. Barto and I am stuck on the following question. The value of a state depends on the the values of the actions possible in that state and on how likely each…
buydadip
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2
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Transformer model conditional probability distribution of sub-sentences

I have a simple transformer model (decoder only) which is trained on some dataset containing sentences to do next-word prediction. The model captures a probability distribution $P_{\theta}(\mathbf{a})$ over a sentence $\mathbf{a}$ by using the chain…
JazzJammer
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2 answers

Which Model for predicting flight delays is appropriate except Random Forest and Decision Tree? (Monte Carlo?)

Im studying M.Sc Data Science and in the module "Decision Support Systems" me and my group have to make a presentation. Our Proposal is the following: Background With generally high demand for runway access and complex organisation required to plan…
wayne
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How to resolve IndexError while doing Monte Carlo for 1000 runs?

Below code runs without any problem, however when I run the same code using Monte Carlo Analysis for 1000 runs, it gives IndexError. Can someone explain why this happens. Thanks X = df1.drop("Gender", axis = 1) y =…
Mathew
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MCMC algorithm -- understanding some paremeters

I am trying to understand an MCMC program. I manage to run it, but I am trying to understand the meaning of the some parameters in the analysis. The code is something like this #Nsamples nsamp = 50000 #Burn-in skip = 300 #temperature at which…
camarman
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How can I build a simulation environment that assess different risk policies?

I work in fin-tech and would like to build some sort of simulation program to assess how different inputs will impact net revenue. For example, if we create new policies based on ML scores, how would those have impacted our loss and revenue…
Kevin
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1 answer

Different results every time I train a reinforcement learning agent

I am training an RL agent for a control problem using PPO algorithm. I am using stable-baselines library for it. The objective of an agent is to maintain a temperature of 24 deg in a zone and it takes actions every 15 mins.The length of episode is…
chink
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Best Method for Data Analysis on a 100 numerical IVs and 200 numerical DVs

I think I might need the help of this valuable community for a task. I have been given a dataset for 100 numerical independent variables (IVs) that predict output for 200 numerical values (from monte carlo simulation results). Which statistical…
UKadir
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