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doi: 10.5281/zenodo.1069094 , 10.5281/zenodo.887179 , 10.5281/zenodo.1406024 , 10.5281/zenodo.2587101 , 10.5281/zenodo.6123307 , 10.5281/zenodo.1217213 , 10.5281/zenodo.5567260 , 10.5281/zenodo.4081371 , 10.5281/zenodo.3965839 , 10.5281/zenodo.998659 , 10.5281/zenodo.7706595 , 10.5281/zenodo.6638428 , 10.5281/zenodo.8366493 , 10.5281/zenodo.4644195 , 10.5281/zenodo.1293542 , 10.5281/zenodo.7705120
doi: 10.5281/zenodo.1069094 , 10.5281/zenodo.887179 , 10.5281/zenodo.1406024 , 10.5281/zenodo.2587101 , 10.5281/zenodo.6123307 , 10.5281/zenodo.1217213 , 10.5281/zenodo.5567260 , 10.5281/zenodo.4081371 , 10.5281/zenodo.3965839 , 10.5281/zenodo.998659 , 10.5281/zenodo.7706595 , 10.5281/zenodo.6638428 , 10.5281/zenodo.8366493 , 10.5281/zenodo.4644195 , 10.5281/zenodo.1293542 , 10.5281/zenodo.7705120
Added the MaxVar acquisition method Added the RandMaxVar acquisition method Added the ExpIntVar acquisition method Implemented the Two Stage Procedure, a method of summary-statistics diagnostics Added new example: the stochastic Lotka-Volterra model Fix methods.bo.utils.minimize to be strictly within bounds Fix elfi.Distance to support scipy 1.0.0
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