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Bayesian optimization in PyTorch

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## Motivation Using `"sample_around_best": True` should lead to improved optimization performance. ### Have you read the [Contributing Guidelines on pull requests](https://github.com/pytorch/botorch/blob/main/CONTRIBUTING.md#pull-requests)? Yest ## Test Plan TODO: Re-run the notebooks, so...

CLA Signed

## Issue description I was following the page of Multi-fidelity BO with discrete fidelities: https://botorch.org/tutorials/discrete_multi_fidelity_bo, and try to add inequality parameter constraints to the optimizer. I only modified the optimize_acqf_mixed()...

Hi, first of all many thanks for such a great and useful library. I am using Botorch for engineering design optimisation combined with CFD simulations and absolutely loving it. I...

enhancement

Dear botorch developers, I have a question regarding output constraints. So far they are used and implemented in the following way: - There is a property which should be larger...

enhancement

# 🚀 Feature Request Add an input constructor for `qNegIntegratedPosteriorVariance`. ## Motivation I'd like to use `qNegIntegratedPosteriorVariance` with Ax and its BoTorch model bridge, but to do so I need...

enhancement

# 🐛 Bug I'm running optimize_acqf_cyclic on a problem with inequality constraints and it seems to be failing in _make_linear_constraints. It seems that the batch_initial_conditions=candidates[i].unsqueeze(0) (line 301) is of shape...

bug

Hi @Balandat, here is a very initial draft of the PR related to #180 . A couple of things: - Normalization and standardization are really important for this function, but...

CLA Signed

# 🐛 Bug Hello, I updated Botorch to the newest version (0.5.0). Before that I was using v0.4.0. The tutorial "Multi-Fidelity BO with Discrete Fidelities using KG" used to work...

bug

## Issue description I am trying to run the turbo_1 from the tutorial : https://botorch.org/tutorials/turbo_1 I used 200D Ackley function as the objective function to be optimized bu turbo_1, and...

The heteroskedastic GP model uses two GPs internally: The first models the observation noise, and the second estimates the function value. As far as I understand, the noise model output...

bug