Main Takeaway: The equivalence between Stein variational gradient descent and black-box In real-world applications, the posterior over the latent variables Z given some data D is usually intractable.

The Challenges In Variational Inference Visualization -

The equivalence between Stein variational gradient descent and black-box In real-world applications, the posterior over the latent variables Z given some data D is usually intractable. VI attempts to find an optimal surrogate posterior by maximizing the Evidence Lower Bound (=ELBO).

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  • The equivalence between Stein variational gradient descent and black-box
  • In real-world applications, the posterior over the latent variables Z given some data D is usually intractable.
  • VI attempts to find an optimal surrogate posterior by maximizing the Evidence Lower Bound (=ELBO).
  • student in the INC Lab, presents his work at the Magnetism and Magnetic Materials 2022 Conference.
  • Recorded at PyData Berlin 2025, Learn how to scale Bayesian models to 50000 time ...

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Visual References

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Sam Liu Presents on Hardware-Aware Bayesian Variational Inference at the MMM 2022 Conference
Scaling Probabilistic Models with Variational Inference
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The equivalence between Stein variational gradient descent and black-box variational inference
Demystifying Variational Inference (Sayam Kumar)
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The challenges in Variational Inference (+ visualization)

The challenges in Variational Inference (+ visualization)

VI attempts to find an optimal surrogate posterior by maximizing the Evidence Lower Bound (=ELBO). The surrogate posterior acts ...

Variational Inference - Explained

Variational Inference - Explained

Read more details and related context about Variational Inference - Explained.

Variational Inference | Evidence Lower Bound (ELBO) | Intuition & Visualization

Variational Inference | Evidence Lower Bound (ELBO) | Intuition & Visualization

In real-world applications, the posterior over the latent variables Z given some data D is usually intractable. But we can use a ...

Variational Inference: Foundations and Innovations

Variational Inference: Foundations and Innovations

Read more details and related context about Variational Inference: Foundations and Innovations.

Deep Learning Lecture 11.2 - Variational Inference

Deep Learning Lecture 11.2 - Variational Inference

Read more details and related context about Deep Learning Lecture 11.2 - Variational Inference.

Sam Liu Presents on Hardware-Aware Bayesian Variational Inference at the MMM 2022 Conference

Sam Liu Presents on Hardware-Aware Bayesian Variational Inference at the MMM 2022 Conference

Sam Liu, Ph.D. student in the INC Lab, presents his work at the Magnetism and Magnetic Materials 2022 Conference.

Scaling Probabilistic Models with Variational Inference

Scaling Probabilistic Models with Variational Inference

Recorded at PyData Berlin 2025, Learn how to scale Bayesian models to 50000 time ...

TILOS Seminar: MCMC vs. variational inference for [...] decision making at scale (2022-02-16)

TILOS Seminar: MCMC vs. variational inference for [...] decision making at scale (2022-02-16)

Read more details and related context about TILOS Seminar: MCMC vs. variational inference for [...] decision making at scale (2022-02-16).

The equivalence between Stein variational gradient descent and black-box variational inference

The equivalence between Stein variational gradient descent and black-box variational inference

The equivalence between Stein variational gradient descent and black-box

Demystifying Variational Inference (Sayam Kumar)

Demystifying Variational Inference (Sayam Kumar)

Read more details and related context about Demystifying Variational Inference (Sayam Kumar).