End-to-end Differentiable Proving
Tim Rocktäschel, Sebastian Riedel
–Neural Information Processing Systems
Current state-of-the-art methods for automated Knowledge Base (KB) completion use neural link prediction models to learn distributed vector representations of symbols ( i.e. subsymbolic representations)
Neural Information Processing Systems
Nov-21-2025, 12:28:25 GMT
- Country:
- Africa > Botswana
- North-West District > Maun (0.04)
- Asia
- China > Beijing
- Beijing (0.04)
- Middle East > Qatar
- South Korea (0.04)
- China > Beijing
- Europe
- France > Auvergne-Rhône-Alpes
- Germany > Berlin (0.04)
- Italy
- Piedmont > Turin Province
- Turin (0.04)
- Sardinia (0.04)
- Piedmont > Turin Province
- Portugal > Lisbon
- Lisbon (0.04)
- Spain > Catalonia
- Barcelona Province > Barcelona (0.04)
- United Kingdom > England
- Oxfordshire > Oxford (0.04)
- Western Europe (0.04)
- North America
- Canada > Quebec
- Montreal (0.04)
- United States
- Arizona > Maricopa County
- Phoenix (0.04)
- California
- Los Angeles County > Long Beach (0.04)
- San Diego County > San Diego (0.04)
- Colorado > Denver County
- Denver (0.04)
- Georgia > Fulton County
- Atlanta (0.04)
- Indiana (0.04)
- Massachusetts > Suffolk County
- Boston (0.04)
- Nevada (0.04)
- Oregon > Benton County
- Corvallis (0.04)
- Arizona > Maricopa County
- Canada > Quebec
- Africa > Botswana
- Genre:
- Research Report (0.48)
- Technology: