IBM Research and ETH Zurich open a new era of innovation
Q & A
Kim Martineau
Quantum Machine Learning
We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud detection. We're doing foundational research in quantum ML to power tomorrow’s smart quantum algorithms.
Our work
IBM welcomes CERN as a new hub in the IBM Quantum Network
ResearchIvano Tavernelli and Panagiotis Barkoutsos7 minute readQuantum kernels can solve machine learning problems that are hard for all classical methods
ResearchYunchao Liu, Srinivasan Arunachalam, and Kristan Temme5 minute readThe power of quantum neural networks
ResearchAmira Abbas, David Sutter, and Stefan Woerner5 minute readIBM Quantum Challenge generates better solutions than challenge creators thought possible
NewsJunye Huang4 minute readThe Discovery Accelerator comes to Europe
NewsAnthony Annunziata, Peter Waggett, and Alessandro Curioni5 minute read- See more of our work on Quantum Machine Learning
Publications
Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits
- Jun Qi
- Chao-han Huck Yang
- et al.
- 2026
- ICASSP 2026
Conference paperTowards quantum extreme learning and reservoir computing on utility-scale digital quantum processors
- Timothée Dao
- Ege Yilmaz
- et al.
- 2026
- APS Global Physics Summit 2026
TalkEfficiently learning depth-3 circuits via quantum agnostic boosting
- Srinivasan Arunachalam
- Arkopal Dutt
- et al.
- 2026
- QIP 2026
TalkPolynomial-time tolerant testing stabilizer states
- Srinivasan Arunachalam
- Arkopal Dutt
- 2026
- QIP 2026
TalkMitigating exponential concentration in covariant quantum kernels for subspace and real-world data
- Gabriele Agliardi
- Giorgio Cortiana
- et al.
- 2025
- npj Quantum Information
PaperShallow entangled circuits for quantum time series prediction on IBM devices
- Mostafizur Rahaman Laskar
- Richa Goel
- 2025
- Nature Scientific Reports
Paper