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Mandala connects electronic-structure learning to observable-guided modeling, enabling direct predictions of critical quantum observables that traditional MLIPs overlook.
Thermal PBE closes the accuracy gap with computationally expensive PIMC for warm dense matter simulations, offering a practical semilocal alternative.
