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Explore visual concept grounding for lifelong learning with Yezhou Yang, delving into active perception and cutting-edge AI research at Arizona State University.
Explore techniques for certifying trustworthiness in deep learning systems with expert insights from Linyi Li, enhancing AI reliability and safety.
Explore human-aware planning and metacognitive AI with insights from Sarath Sreedharan, focusing on incomplete model-knowledge and AI-human interaction.
Explore pro-social language models with Dartmouth's Soroush Vosoughi, examining their potential for positive societal impact and ethical AI development.
Explore deep ontological networks, focusing on recursive reasoning networks and their applications through an in-depth overview and experimental insights.
Explore scene graphs and current research in this field, gaining insights into an exciting area of AI and machine learning.
Explore language agents as a critical evolutionary step in AI, focusing on LLM research and its implications for advancing artificial intelligence capabilities.
Explore the intersection of symbolic methods and deep learning in AI, covering algorithms, Python packages, and progress towards AGI in this comprehensive introduction.
Explore probabilistic circuits with YooJung Choi, delving into advanced AI concepts at the intersection of symbolic methods and deep learning.
Explore abductive learning through key papers, covering concepts, new developments, and related research in neuro-symbolic AI. Gain insights into this exciting field at the intersection of symbolic methods and deep learning.
Explore human-centered explainable AI with Professor Mark Reidl, focusing on key concepts, latest research, and practical applications in this emerging field of artificial intelligence.
Explore neurosymbolic approaches to Inductive Logic Programming, covering key concepts, architectures, and experimental results from a seminal 2018 paper.
Explore symbolic reasoning using language model agents in this talk by Prof. Swarat Chaudhuri. Gain insights into cutting-edge research at the intersection of AI and symbolic methods.
Explore AI introspection approaches from ML and KR perspectives, covering ICNs, generative vs. discriminative models, and concept induction for enhanced machine learning understanding.
Explore classic AI search algorithms, from uninformed to advanced techniques, with insights on problem-solving strategies and heuristic development.
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