Induction for SMT Solvers

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Neuro-symbolic Representations: Commonsense Knowledge & Reasoning

Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.

Verifying Programs with Stainless: How Stainless Works

Explores the inner workings of the Stainless framework, emphasizing verification-aware transformations and dependent type checking.

Quantum Machine Learning: Theory and Applications

Explores quantum machine learning, representations of molecules, kernel regression, and the interplay between physics and machine learning.

Uncertain Reasoning: Bayesian Networks

Explores uncertain reasoning, Bayesian networks, and stochastic resolution, emphasizing the importance of probabilistic logic and abduction.

Counterexample to Induction Theorem

Explores a counterexample to the induction principle, demonstrating a property of natural numbers.

Transforms of the Place

Explores the intuition behind transforms of the place and addresses audience questions on integral calculations and function choices.

Mathematical Induction: Principle and Example

Introduces the principle of mathematical induction through an example.

Beliefs: Definition and Mechanisms

Delves into the definition of beliefs, the influence on behavior, classification, and the relationship with science.

Presburger Arithmetic and Quantifier Elimination

Covers Presburger arithmetic, quantifier elimination, and the transformation of formulas into disjunctive normal form.

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