update papers (#1522)

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Pull Request resolved: #1522

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## Related PRs

(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/pytorch/botorch, and link to your PR here.)

Reviewed By: sdaulton

Differential Revision: D41522457

Pulled By: Balandat

fbshipit-source-id: f3525688a39b3452bbe17de790477e5f6d308e53

Author: eytan

docs/papers.md

@@ -18,24 +18,45 @@ The main reference for BoTorch is
 
 Here is an incomplete selection of peer-reviewed Bayesian optimization papers that build off of BoTorch:
 
+- [Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization](https://arxiv.org/pdf/2210.10199.pdf). Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne, Eytan Bakshy. NeurIPS 2022.
+- [Robust Multi-Objective Bayesian Optimization Under Input Noise](https://arxiv.org/pdf/2202.07549.pdf). Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy. ICML 2022.
+
+- [Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces](https://arxiv.org/pdf/2109.10964.pdf).
+Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy. UAI 2022.
+
+- [Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes](https://arxiv.org/pdf/2203.11382.pdf).
+Jerry Lin, Raul Astudillo, Peter Frazier, Eytan Bakshy. AISTATS 2022.
+
+- [Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation](https://arxiv.org/pdf/2203.09751.pdf).
+Benjamin Letham, Eytan Bakshy, Michael Shvartsman. AISTATS 2022.
+
+- [GIBBON: General-purpose Information-Based Bayesian OptimisatioN](https://jmlr.org/papers/volume22/21-0120/21-0120.pdf). Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson. JMLR 2021.
+- [Conditioning Sparse Variational Gaussian Processes
+for Online Decision-making](https://proceedings.neurips.cc/paper/2021/file/325eaeac5bef34937cfdc1bd73034d17-Paper.pdf). Wesley J. Maddox, Samuel Stanton, and Andrew G. Wilson. NeurIPS 2021
+
+- [Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs](https://arxiv.org/pdf/2111.06537.pdf).
+Raul Astudillo, Daniel Jiang, Maximilian Balandat, Eytan Bakshy, Peter Frazier. NeurIPS 2021.
+
+- [Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement](https://arxiv.org/pdf/2105.08195.pdf).
+Samuel Daulton, Max Balandat, Eytan Bakshy. NeurIPS 2021.
+
+- [Bayesian Optimization of Risk Measures](https://proceedings.neurips.cc/paper/2020/hash/e8f2779682fd11fa2067beffc27a9192-Abstract.html). Sait Cakmak, Raul Astudillo Marban, Peter Frazier, Enlu Zhou. NeurIPS 2020.
+
 - [Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization](https://proceedings.neurips.cc/paper/2020/hash/6fec24eac8f18ed793f5eaad3dd7977c-Abstract.html). Sam Daulton, Maximilian Balandat, Eytan Bakshy. NeurIPS 2020.
-- [Bayesian Optimization of Risk Measures
-](https://proceedings.neurips.cc/paper/2020/hash/e8f2779682fd11fa2067beffc27a9192-Abstract.html). Sait Cakmak, Raul Astudillo Marban, Peter Frazier, Enlu Zhou. NeurIPS 2020.
-- [High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
-](https://proceedings.neurips.cc/paper/2020/hash/faff959d885ec0ecf70741a846c34d1d-Abstract.html). Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy. NeurIPS 2020.
-- [High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds](https://proceedings.neurips.cc/paper/2020/hash/f05da679342107f92111ad9d65959cd3-Abstract.html). Noémie Jaquier, Leonel Rozo. NeurIPS 2020.
 - [Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees](https://proceedings.neurips.cc/paper/2020/hash/d1d5923fc822531bbfd9d87d4760914b-Abstract.html). Shali Jiang, Daniel Jiang, Maximilian Balandat, Brian Karrer, Jacob Gardner, Roman Garnett. NeurIPS 2020.
+- [High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds](https://proceedings.neurips.cc/paper/2020/hash/f05da679342107f92111ad9d65959cd3-Abstract.html). Noémie Jaquier, Leonel Rozo. NeurIPS 2020.
+- [High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization](https://proceedings.neurips.cc/paper/2020/hash/faff959d885ec0ecf70741a846c34d1d-Abstract.html). Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy. NeurIPS 2020.
 - [Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization](https://proceedings.neurips.cc/paper/2020/hash/10fb6cfa4c990d2bad5ddef4f70e8ba2-Abstract.html). Ben Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy. NeurIPS 2020.
 - [PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks
 ](https://arxiv.org/abs/2007.11752). Ting-Wu Chin, Ari S. Morcos, Diana Marculescu. ICML 2020 Workshop on Real World Experiment Design and Active Learning.
-- [High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces
-](https://proceedings.mlr.press/v161/eriksson21a.html). David Eriksson, Martin Jankowiak. UAI 2021.
+- [High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces](https://proceedings.mlr.press/v161/eriksson21a.html). David Eriksson, Martin Jankowiak. UAI 2021.
 - [Bayesian Optimization over Permutation Spaces](https://arxiv.org/abs/2112.01049). Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim. AAAI 2021.
-- [GIBBON: General-purpose Information-Based Bayesian Optimisation](https://jmlr.org/papers/v22/21-0120.html). Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson. JMLR, 2021.
+- [Bayesian Optimization of Function Networks](https://papers.nips.cc/paper/2021/hash/792c7b5aae4a79e78aaeda80516ae2ac-Abstract.html). Raul Astudillo, Peter Frazier. NeurIPS 2021.
 - [Bayesian Optimization with High-Dimensional Outputs](https://papers.nips.cc/paper/2021/hash/a0d3973ad100ad83a64c304bb58677dd-Abstract.html). Wesley J. Maddox, Maximilian Balandat, Andrew G. Wilson, Eytan Bakshy. NeurIPS 2021.
-- [Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement](https://papers.nips.cc/paper/2021/hash/11704817e347269b7254e744b5e22dac-Abstract.html). Samuel Daulton, Maximilian Balandat, Eytan Bakshy. NeurIPS 2021.
 - [Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces](https://papers.nips.cc/paper/2021/hash/44e76e99b5e194377e955b13fb12f630-Abstract.html). Aryan Deshwal, Jana Doppa. NeurIPS 2021.
-- [Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs](https://papers.nips.cc/paper/2021/hash/a8ecbabae151abacba7dbde04f761c37-Abstract.html). Raul Astudillo, Daniel Jiang, Maximilian Balandat, Eytan Bakshy, Peter Frazier. NeurIPS 2021.
-- [Bayesian Optimization of Function Networks](https://papers.nips.cc/paper/2021/hash/792c7b5aae4a79e78aaeda80516ae2ac-Abstract.html). Raul Astudillo, Peter Frazier. NeurIPS 2021.
 - [Improving black-box optimization in VAE latent space using decoder uncertainty](https://papers.nips.cc/paper/2021/hash/06fe1c234519f6812fc4c1baae25d6af-Abstract.html). Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal. NeurIPS 2021
+- [Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs](https://papers.nips.cc/paper/2021/hash/a8ecbabae151abacba7dbde04f761c37-Abstract.html). Raul Astudillo, Daniel Jiang, Maximilian Balandat, Eytan Bakshy, Peter Frazier. NeurIPS 2021.
+- [Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement](https://papers.nips.cc/paper/2021/hash/11704817e347269b7254e744b5e22dac-Abstract.html). Samuel Daulton, Maximilian Balandat, Eytan Bakshy. NeurIPS 2021.
 - [Risk-averse Heteroscedastic Bayesian Optimization](https://papers.nips.cc/paper/2021/hash/8f97d1d7e02158a83ceb2c14ff5372cd-Abstract.html). Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause. NeurIPS 2021.
+
+*Please feel free to add any other peer reviewed works that build off of botorch via a PR!*