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Academia-Industry Matching Event (AIME24)

21–22 Nov 2024
Mercure Budapest Castle Hill Hotel
Europe/Budapest timezone

Contribution List

25 out of 25 displayed
  1. 7. Welocme and Opening
    Roland Jakab (HUN-REN)
    21/11/2024, 09:00
  2. 22. Quantum Communication Research at the Budapest University of Technology and Economics
    Dr Eszter Udvary (Budapest University of Technology and Economics)
    21/11/2024, 09:30
  3. 6. MILAB - Synergies between academic research and industrial needs
    Gábor Érdi-Krausz (HUN-REN SZTAKI)
    21/11/2024, 09:50
  4. 3. A Novel Approach to Intelligent Systems
    Antal Jakovác (WIGNER RCP)
    21/11/2024, 10:25

    Mainstream artificial intelligence (AI) solutions, while achieving considerable success in areas such as classification, generation, and natural language understanding, still face several notorious, long-standing challenges. These include unexpected classification errors, hallucinations in generative models, and catastrophic forgetting, among others.

    Addressing these issues requires...

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  5. 5. On the Causality Paradox in Large Language Models: The Known Unknowns
    Péter Antal (Budapest University of Technology and Economics)
    21/11/2024, 11:30

    Large language models (LLMs) face challenges with complex
    probabilistic, causal, and counterfactual reasoning, yet they
    demonstrate promising capabilities in the automated construction of both
    qualitative and quantitative probabilistic and causal models. This talk
    provides an overview of current benchmarks for causal reasoning in LLMs,
    methods for extracting knowledge from LLMs,...

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  6. 4. AI Applications with BOSCH
    Hunor István Lukács (Eötvös University)
    21/11/2024, 12:00
  7. 16. Unified theory of temporal causal discovery
    Andras Telcs
    21/11/2024, 12:30

    Temporally evolving systems are typically modeled by dynamic equations. A
    key challenge in accurate modeling is understanding the causal relationships between subsystems, as well as identifying the presence and influence of unobserved hidden drivers on the observed dynamics. This paper presents a unified method capable of identifying fundamental causal relationships between pairs of systems,...

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  8. 8. Unlocking High-Performance AI Inference with Dense Tensor Computing on Groq's LPU
    Ernesto Bonomi (Groq Inc.)
    21/11/2024, 14:00
  9. 26. On the learning abilities of photonic continuous-variable Born machines
    Zoltán Kolarovszki
    21/11/2024, 14:30

    We investigate photonic continuous-variable Born machines (CVBMs), which utilize photonic quantum states as resources for continuous probability distributions. Implementing exact gradient descent in the CVBM training process is often infeasible, bringing forward the need to approximate the gradients using an estimator obtained from a smaller number of samples, obtaining a quantum stochastic...

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  10. 10. AQMLator--An Auto Quantum Machine Learning E-Platform
    Tomasz Rybotycki (Center of Excellence in Artificial Intelligence, AGH University, Cracow)
    21/11/2024, 15:00
  11. 9. Building a Quantum Computer Simulator based on Groq chips
    Peter Rakyta (Department of Physics of Complex Systems, Eötvös Loránd University)
    21/11/2024, 16:00
  12. 12. Hybrid Quantum-Classical Reinforcement Learning in Latent Observation Spaces
    Daniel Nagy (HUN-REN Wigner Reasearch Centre for Physics)
    21/11/2024, 16:30
  13. 13. Theoretical high-energy physics and AI
    Matthew Schwartz (Harvard University)
    21/11/2024, 16:55
  14. 17. Chemical simulations: from academics to industry
    Tibor Holtz (Furukawa LTD)
    22/11/2024, 09:00

    Reactivity is a fundamental aspect of various processes,
    including chemical vapor deposition and catalysis. Computer simulations
    have become indispensable in modern industrial development,
    serving not only to shorten research and development timelines but also to
    deepen our understanding of these processes. The advent of advanced
    quantum chemical and force field-based methods,...

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  15. 18. Quantum Phase Transitions: A Qutrit Perspective and Novel Order Parameter Discovery
    Enrique Rico Ortega (CERN)
    22/11/2024, 09:45

    Quantum phase transitions and symmetry-protected topological
    phases remain at the forefront of quantum physics research. This
    presentation highlights recent advancements in these fields, focusing on
    two key contributions:
    - Realizing the Haldane Phase with Qutrits: We
    discuss the successful creation of the spin-1 Haldane phase on a qudit
    quantum processor, as detailed in...

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  16. 19. Tensor Network methods via AI accelerators
    Andor Menczer (ELTE, HUN-REN Wigner RCP)
    22/11/2024, 10:30
  17. 20. Advanced Tensor Network methods in HPC systems
    Artur Garcia (Barcelona Supercomputing Center)
    22/11/2024, 11:30
  18. 21. Quantum Computing in Practice
    Robert Izsak (Riverlane LTD)
    22/11/2024, 12:15

    In this contribution, I will briefly discuss the differences and
    similarities between industrial and academic research and provide an
    example of a joint project on magnetic systems and quantum computing.
    Furthermore, I will summarize the most relevant research papers published
    in our group on quantum computing, including those on embedding, the cost
    analysis of pharmaceutical and...

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  19. 25. A Novel Approach to Intelligent Systems
    Antal Jakovac (Wigner RCP, Department of Computational Sciences)

    Mainstream artificial intelligence (AI) solutions, while achieving considerable success in areas such as classification, generation, and natural language understanding, still face several notorious, long-standing challenges. These include unexpected classification errors, hallucinations in generative models, and catastrophic forgetting, among others.

    Addressing these issues requires...

    Go to contribution page
  20. 24. AI Solutions: ELTE and Bosch Partnership
    Hunor István Lukács (Eötvös Loránd University, Robert Bosch Kft.)

    The ELTE AI Department, in collaboration with Bosch, addresses industrial challenges by leveraging AI expertise to develop innovative solutions, such as autonomous driving and production optimization in factories. One of these projects focuses on welding line detection. In modern industrial settings, accurately identifying and verifying welding lines is essential for ensuring product quality....

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  21. 1. On the learning abilities of photonic continuous-variable Born machines
    Zoltán Kolarovszki

    We investigate photonic continuous-variable Born machines (CVBMs), which utilize photonic quantum states as resources for continuous probability distributions. Implementing exact gradient descent in the CVBM training process is often infeasible, bringing forward the need to approximate the gradients using an estimator obtained from a smaller number of samples, obtaining a quantum stochastic...

    Go to contribution page
  22. 23. Quantum Phase Transitions: A Qutrit Perspective and Novel Order Parameter Discovery
    Dr Enrique Rico Ortega (CERN)

    Quantum phase transitions and symmetry-protected topological phases remain at the forefront of quantum physics research. This presentation highlights recent advancements in these fields, focusing on two key contributions:

    • Realizing the Haldane Phase with Qutrits: We discuss the successful creation of the spin-1 Haldane phase on a qudit quantum processor, as detailed in arXiv:2408.04702....
    Go to contribution page
  23. 14. TBA
  24. 15. TBA
  25. 2. Unified theory of temporal causal discovery
    Andras Telcs

    Temporally evolving systems are typically modeled by dynamic equations. A
    key challenge in accurate modeling is understanding the causal relationships between subsystems, as well as identifying the presence and influence of unobserved hidden drivers on the observed dynamics. This paper presents a unified method capable of identifying fundamental causal relationships between pairs of systems,...

    Go to contribution page